In this role, you will lead teams responsible for robotics platform software, system integration, reference platform development, platform bring-up, validation, and deployment. You will work closely with NVIDIA's global robotics teams to develop and deliver reference platforms that enable embodied AI systems to be deployed at scale.

Responsibilities:

• Build and lead NVIDIA's Robotics Platform Engineering team in China, based in Shanghai.
• Recruit, mentor, and develop outstanding engineering talent, including technical leads and senior engineers.
• Define the technical strategy, organizational priorities, and execution roadmap for next-generation robotics reference platforms.
• Drive end-to-end system integration across robotics software stacks, including perception, control, foundation models, learning-based policies, runtime systems, and cloud-connected services.
• Lead platform bring-up and validation across compute modules, cameras, sensors, networking, safety systems, and robotic subsystems.
• Define scalable reference platform architectures that can be adopted across multiple robot vendors, form factors, and deployment scenarios.
• Partner closely with AI, simulation, hardware, product, platform, and ecosystem teams to align roadmaps and execution.
• Work directly with strategic robotics partners and customers to accelerate platform adoption and real-world deployment.

Requirements:

• MS or PhD degree in Computer Science, Electrical Engineering, Computer Engineering, Robotics, or a related field, or equivalent experience.
• 8+ overall years of experience developing robotics, embedded, platform, distributed, or systems software.
• 3+ years of engineering management experience leading software or systems engineering teams and running complex programs across multiple functions.
• Strong understanding of robotics system architecture, platform software, and hardware and software integration.
• Experience bringing up and deploying complex robotic systems on physical hardware.
• Strong understanding of Linux systems, embedded software, distributed computing, and real-time systems.
• Strong communication, leadership, and organizational skills.
• Ability to influence decisions and align collaborators across global organizations.

Preferred Qualifications:

• Experience building and shipping humanoid robotic systems and reference platforms adopted by customers, partners, or ecosystem developers.
• Experience deploying foundation models, embodied AI models, or reinforcement learning policies on physical robots.
• Experience leading globally distributed engineering teams across multiple sites and regions.
• Strong background in perception, sensor integration, performance optimization, and system validation.
• Experience defining platform strategy across multiple hardware generations and product roadmaps.

NVIDIA offers competitive salaries and comprehensive benefits for you and your family.

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You will grow and develop a dynamic team with expertise in areas including enterprise software, data engineering, and data science/machine learning, who will continue to deepen their knowledge of Databricks as the platform expands.

You will guide and get involved to enhance your team's effectiveness; be an expert at communicating complex, business value-focused solutions; support complex sales cycles and customer architectures; and build relationships with key stakeholders in large corporations.

The SSA Team is engaged in our most important and complex customer engagements, providing deep technical expertise to both new and existing customers.

Your team provides specialist expertise to the Solution Architect (SA) and Sales teams, which are responsible for developing and overseeing the overall technical account strategy.

Reporting to the Director, Field Engineering.

The impact you will have:

• You will hire, train, and grow a diverse team of Specialist Solutions Architects for Databricks, a company in hyper-growth mode
• Exceed your region's consumption targets - by working with your cross-functional counterparts to determine where to deploy your team of technical experts to drive the most critical use cases forward
• Make your customers extremely successful with Databricks and provide outsized value to their businesses
• Establish relationships across the business to make your customers and team successful
• Grow Databricks Platform usage and prevent churn in strategic accounts by overseeing and retiring a regional growth quota
• Create positive morale for the team and help foster a working relationship between Field Engineering, Sales, and other important internal partners
• Help resolve customer questions and concerns on accounts and opportunities deemed strategic by Sales and Pre-sales field leadership
• Act in a supportive manager capacity, including handling escalations, mentoring team members, building a career path for the assigned team members, etc.

What we look for:

• 5+ years of experience leading Data & AI Engineering teams, technical pre-sales and/or post-sales teams, with a proven track record in the management of elite technical individual contributors.
• 5+ years of hands-on experience in developing data solutions with highly technical platforms (e.g., distributed computing, cloud data warehousing, MLOps, Generative AI infrastructure).
• Strong skillset in technical discovery, architecture design validation, structured proof-of-concept (POC/MVP) management, and value-selling frameworks.
• Trusted advisor to technical executives who guide strategic data infrastructure decisions
• Team player, but able to challenge and define priorities.
• Self-starter, challenger, strategic planner & analytical thinker.
• Experience hiring qualified candidates, ramping them up to be successful, and promoting into larger roles.
• Experience working with other teams such as Sales, Product Management, and Forward Deployed Engineering teams.
• Native proficiency in Korean is a must and business level English is preferred

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Key Responsibilities:

• Frontline Support: Serve as the primary technical point of contact for escalated issues related to the Databricks Data Intelligence platform. Provide expert-level troubleshooting, diagnostics, and resolution for complex problems affecting system performance and reliability.
• Customer Interaction: Engage with customers directly to understand their technical issues and requirements. Provide timely, clear, and actionable solutions to ensure high levels of customer satisfaction.
• Incident Management: Lead the resolution of high-priority incidents, coordinating with various teams to address and mitigate issues swiftly. Conduct thorough root cause analyses and develop preventive measures to avoid recurrence.
• Collaboration: Work closely with engineering, product management, and DevOps teams to share insights, identify recurring issues, and drive improvements to the Databricks Data Intelligence platform.
• Documentation and Knowledge Sharing: Create and maintain detailed documentation on support procedures, known issues, and solutions. Contribute to internal knowledge bases and create training materials to assist other support engineers.
• Performance Monitoring: Monitor and analyze platform performance metrics to identify potential issues before they impact customers. Implement optimizations and enhancements to improve platform stability and efficiency.
• Platform Upgrades: Manage and oversee the deployment of Databricks Data Intelligence platform upgrades and patches, ensuring minimal disruption to services and maintaining system integrity.
• Innovation and Improvement: Stay abreast of industry trends and advancements in Databricks technology. Propose and drive initiatives to enhance platform capabilities and support processes.
• Customer Feedback: Collect and analyze customer feedback to drive continuous improvement in support processes and platform features.

Qualifications:

• Experience: Minimum of 7 years of hands-on experience in a technical support or engineering role related to Databricks Data Intelligence platform, cloud data platforms, or big data technologies.
• Technical Skills: A deep understanding of Databricks architecture and Apache Spark, along with experience in cloud platforms like AWS, Azure, or GCP, is essential. Strong capabilities in designing and managing data pipelines, distributed computing are required. Proficiency in Unix/Linux administration, familiarity with DevOps practices, and skills in log analysis and monitoring tools are also crucial for effective troubleshooting and system optimization.
• Problem-Solving: Demonstrated ability to diagnose and resolve complex technical issues with a strong analytical and methodical approach.
• Communication: Exceptional verbal and written communication skills, with the ability to effectively convey technical information to both technical and non-technical stakeholders.
• Customer Focus: Proven experience in managing high-impact customer interactions and ensuring a positive customer experience.
• Collaboration: Ability to work effectively in a team environment, collaborating with engineering, product, and customer-facing teams.
• Education: Bachelor’s degree in Computer Science, Engineering, or a related field. Advanced degree or relevant certifications are highly desirable.

Preferred Skills:

• Experience with additional big data tools and technologies such as Hadoop, Kafka, or NoSQL databases.
• Familiarity with automation tools and CI/CD pipelines.
• Understanding of data governance and compliance requirements.

Why Join Us?

• Innovative Environment: Work with cutting-edge technology in a fast-paced, innovative company.
• Career Growth: Opportunities for professional development and career advancement.
• Team Culture: Collaborate with a talented and motivated team dedicated to excellence and continuous improvement.

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Key Responsibilities:

• Design and maintain unified profiling frameworks for CPU and GPU environments.
• Conduct in-depth benchmarking of EDA applications to analyze memory access patterns and instruction-level parallelism.
• Use GPU profilers to identify inefficiencies such as warp divergence and PCIe/NVLink bottlenecks.
• Develop tools to monitor and optimize high-watermark memory usage in multi-terabyte EDA builds.
• Create predictive models to guide hardware procurement and cloud instance selection.

Requirements:

• Experience with CUDA programming and GPU profiling tools like NVIDIA Nsight Systems/Compute.
• Knowledge of profiling tools such as perf, eBPF, VTune, or Valgrind.
• Strong benchmarking skills and ability to analyze complex performance data.
• Experience with distributed compute environments like Slurm, LSF, or Kubernetes.
• BS, MS, or PhD in Computer Science, Electrical Engineering, or related field with 8+ years of relevant experience.

NVIDIA offers competitive salaries and a comprehensive benefits package, including equity.

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

The impact you will have:

• Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
• Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications
• Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks
• Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs
• Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact
• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap

What we look for:

• 6+ years experience in data engineering, data platforms & analytics, or software engineering
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps, ML/AI models and AI APIs
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions
• Documentation and white-boarding skills
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects
• Travel to customers 20% of the time
• Databricks Certification

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Responsibilities

• Design and implement data processing infrastructure for large language model training (highly performant, reproducible, traceable)
• Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability
• Build robust systems for data quality assurance and validation at scale
• Collaborate with research teams to implement novel data processing architectures
• Build and operate end-to-end data pipelines that turn raw web-scale corpora into training-ready datasets

Requirements

• 5+ YOE outside of internships
• Strong software engineering skills with experience building high-throughput fault-tolerant distributed systems
• Hands-on experience with distributed computing frameworks, particularly Apache Spark
• Excellent problem-solving skills and attention to detail
• Strong communication skills and ability to work in a collaborative environment
• Advanced degree in Computer Science or related field
• Experience with language model training infrastructure
• Background in Data Infrastructure, MLOps, or ML infrastructure

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
• Visa sponsorship: We do sponsor visas!

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As an AI Architect, you are responsible for designing and implementing advanced Artificial Intelligence (AI/ML/GenAI) solutions that align with business objectives.

Responsibilities:

• Develop and maintain AI/ML/GenAI architecture aligned with organisational goals.
• Identify opportunities for AI adoption and create strategic plans for implementation.
• Design and implement AI and machine learning (ML) models to solve complex business problems.
• Select appropriate AI frameworks, tools, and technologies.
• Develop reusable AI and GenAI capabilities and infrastructure, including MCP servers, RAG framework, Agentic Framework, A2A protocols, A2M protocol, and Model as APIs.
• Collaborate with data scientists, engineers, and business stakeholders to integrate AI into products and services.
• Establish best practices for AI model development, deployment, and maintenance using MLOps and LLMOps.
• Monitor AI system performance and optimise platform scalability, efficiency, and accuracy.
• Conduct experiments, validate models, and improve existing AI solutions.
• Provide technical leadership and mentorship to team members.
• Work cross-functionally to ensure cohesive development and deployment of AI solutions.
• Stay up to date with advancements in AI, ML, Generative AI, MLOps, and LLMOps.
• Research emerging technologies and recommend adoption strategies.

Requirements:

• Strong knowledge and working experience of Machine Learning, Deep Learning, Natural Language Processing (NLP), LLMs, Agentic flows (LangChain, LangGraph), and Prompt engineering.
• Proficiency in frameworks like TensorFlow, PyTorch, and libraries for AI/ML.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps, LLMOps practices (MLFlow 3.0 and similar experience is a plus).
• Expertise in Python, R, and data engineering concepts.
• Understanding of data architecture, model deployment, and scalable AI systems.
• Familiarity with big data technologies and distributed computing, experience on Databricks DE and AI/ML stack is a plus.
• Must have experience on developing and implementing GenAI projects in production.
• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder management abilities.
• Experience in building AI/GenAI solutions in insurance/financial institutions is a plus.

Working Experience:

• 7+ years of experience in AI/ML/GenAI development and architecture, experience in Generative AI, LLMs, and cloud-native AI solutions, and knowledge of data governance, security, and compliance in AI systems.

Professional Qualifications:

• Certifications related to AI/GenAI would be an added advantage.

Education:

• Master's/Bachelor's degree in STEM (Science, Technology, Engineering, Mathematics).

Language:

• Fluency in written and spoken English.

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You will develop new software and hardware approaches, shape platform evolution through hands-on innovation, and contribute to designing systems powering the fastest AI workloads globally. Collaborate with our distinguished team of researchers and engineers building software and hardware for AI at an outstanding scale.

Responsibilities:

• Build and evolve the architecture of scalable software systems for distributed AI training and inference, focusing on throughput, latency, resiliency, and memory efficiency across cluster-scale deployments.
• Develop and evaluate next-generation communication and runtime capabilities in libraries such as NCCL, UCX, and UCC, tailored to the evolving demands of frontier AI workloads.
• Partner with AI framework teams (e.g., TensorFlow, PyTorch, JAX) and internal platform teams to build integrations, explore new approaches, and improve end-to-end performance and reliability.
• Collaborate on hardware and system-level features across GPUs, DPUs, and interconnects to speed up data movement and enable new capabilities for training, inference, and model serving at scale.
• Drive innovation across runtime systems, communication libraries, and AI-specific protocol layers, helping turn new ideas into practical capabilities and robust implementations.

Requirements:

• Ph.D., or equivalent industry experience, in computer science, computer engineering, or a closely related field.
• 5+ years of experience in systems programming, parallel or distributed computing, high-performance networking, or large-scale data movement, including experience designing and building complex systems.
• Strong programming background in C++, Python, and ideally CUDA or other GPU programming models, with a track record of building production-quality performance-critical software.
• Extensive hands-on experience with AI frameworks (e.g., PyTorch, TensorFlow, JAX) and a solid grasp of how communication libraries and runtime systems facilitate large-scale training and inference.
• Demonstrated success in developing and refining high-throughput, low-latency systems, including the ability to reason across software stacks, hardware capabilities, and system bottlenecks.
• Strong collaboration skills in a multi-national, interdisciplinary setting, with the ability to contribute ideas, build momentum, and work effectively with senior engineers, researchers, and partner teams.

Benefits:

NVIDIA offers highly competitive salaries and a comprehensive benefits package. You can learn more about our benefits at www.nvidiabenefits.com/

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

Your responsibilities will include:

• Production Solution Delivery: Leading impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications, and data ingestion and ML/AI model integration.
• Transformational Impact: Guiding strategic customers as they implement transformational big data projects, including end-to-end design, build, and deployment of industry-leading big data and AI applications.
• Empower Customers: Guiding customers on architecture and design, bootstrapping or implementing customer projects that lead to successful understanding, evaluation, and adoption of Databricks.
• Own the Architecture: Leading architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Collaboration: Working with the Databricks technical team, Project Manager, Architect, and Customer team to ensure technical components of the engagement are delivered to meet customer's needs.
• Feedback and Resolution: Working with Engineering and Databricks Customer Support to provide product and implementation feedback and guide rapid resolution for engagement-specific product and support issues.
• Customer Immersion: Embedding with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contributing accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Requirements:

• 6+ years of experience in data engineering, data platforms & analytics, or software engineering.
• Proficiency in writing code in languages such as Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models, and AI APIs.
• Experience with technical project delivery, managing scope, timelines, and measurable outcomes.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Ability to travel to customers 20% of the time.
• Databricks Certification.

We offer comprehensive benefits and perks that meet the needs of all our employees, details of which can be found on our website.

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

The impact you will have:

• Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration.
• Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications.
• Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models and AI APIs.
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time.
• Databricks Certification.

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes.

The impact you will have:

• Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications, and data ingestion and ML/AI model integration.
• Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end-to-end design, build, and deployment of industry-leading big data and AI applications.
• Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which lead to a customer's successful understanding, evaluation, and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect, and Customer team to ensure the technical components of the engagement are delivered to meet the customer's needs.
• Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

• 6+ years in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models, and AI APIs.
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines, and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time.
• Databricks Certification.

Pay Range Transparency The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Zone 1 Pay Range: $182,000-$250,208 USD Zone 2 Pay Range: $182,000-$250,208 USD Zone 3 Pay Range: $182,000-$250,208 USD Zone 4 Pay Range: $182,000-$250,208 USD

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This role combines strong software engineering practices with expertise in large-scale data processing and advanced analytical methods to deliver reliable, scalable solutions across the organization.

Responsibilities:

• Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc.
• Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement.
• Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows.
• Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights.
• Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics.
• Implement monitoring, alerting, and automation for data systems to support real-time decision support.
• Mentor team members on best practices for scalable data engineering and quantitative problem-solving.

Basic Qualifications:

• 4+ years of experience building production data pipelines and infrastructure at scale.
• Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).
• Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
• Solid understanding of cloud services for data storage, processing, and orchestration.
• Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
• Excellent problem-solving skills with a focus on delivering business impact through reliable systems.

Preferred Skills and Experience:

• Prior work in consumer technology, or social media domains.
• Experience with real-time streaming systems and low-latency data processing.
• Contributions to open-source data tools or publications on large-scale analytics systems.
• Track record of reducing operational costs or improving system efficiency through data optimizations.
• Ability to bridge engineering excellence with rigorous analytical approaches.

Compensation and Benefits:

The salary range is $180,000 - $440,000 USD. The total rewards package at xAI also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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We are seeking a skilled Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making.

Responsibilities:

• Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc.
• Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement.
• Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows.
• Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights.
• Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics.
• Implement monitoring, alerting, and automation for data systems to support real-time decision support.
• Mentor team members on best practices for scalable data engineering and quantitative problem-solving.

Basic Qualifications:

• 4+ years of experience building production data pipelines and infrastructure at scale.
• Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).
• Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
• Solid understanding of cloud services for data storage, processing, and orchestration.
• Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
• Excellent problem-solving skills with a focus on delivering business impact through reliable systems.

Preferred Skills and Experience:

• Prior work in consumer technology or social media domains.
• Experience with real-time streaming systems and low-latency data processing.
• Contributions to open-source data tools or publications on large-scale analytics systems.
• Track record of reducing operational costs or improving system efficiency through data optimizations.
• Ability to bridge engineering excellence with rigorous analytical approaches.

Compensation and Benefits:

The salary range is $180,000 - $440,000 USD. The total rewards package at xAI also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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You will independently own meaningful platform components and lead projects from problem discovery and technical design through production deployment and adoption. You will collaborate with NVIDIA teams around the world and influence how we evaluate evolving areas such as large language models, agentic AI, accelerated computing, and other emerging AI workloads.

Responsibilities

• Define the technical direction and architecture for major areas of PerfLab's benchmark infrastructure, translating evolving business and engineering needs into clear roadmaps and scalable platform capabilities.
• Lead the design and implementation of reusable software, services, and workflows that automate benchmark definition, execution, result collection, validation, and reporting across local, cluster, and cloud-native environments.
• Remain hands-on with performance testing and analysis, developing a deep understanding of existing workflows and using that knowledge to guide platform investments and technical decisions.
• Establish engineering approaches that improve the reliability, scalability, observability, maintainability, and reproducibility of large benchmark campaigns.
• Lead the diagnosis of complex, cross-layer issues spanning applications, Linux systems, containers, distributed jobs, compute resources, networking, and storage.
• Build strong partnerships with performance engineers, QA teams, product teams, and other customers; create alignment across organizations and drive high-impact ideas and projects from concept through adoption.
• Provide technical leadership through architecture and code reviews, clear decision-making, high engineering standards, and mentoring of other engineers.
• Identify emerging technologies, including AI-assisted automation, and determine where they can deliver meaningful improvements in benchmark creation, failure triage, data analysis, or engineering productivity.
• Contribute to the strategy and development of internal and open-source infrastructure projects, and help grow their adoption across teams.

Requirements

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent practical experience.
• 6+ years of relevant software engineering experience in system software, infrastructure, developer platforms, distributed systems, or production automation.
• Strong Python programming and software engineering expertise, with a track record of building and operating production-quality tools, services, or automation frameworks.
• Solid understanding of Linux and system-level concepts such as processes, concurrency, networking, storage, resource management, and failure handling.
• Extensive experience with containers and workload orchestration, scheduling, or distributed computing platforms, including the design of reliable systems with clear interfaces, testing, observability, and recovery behavior.
• Knowledge of machine learning, AI, or accelerated-computing workloads and experience reasoning about their performance, quality, and operational tradeoffs.
• Proven technical leadership on sophisticated, multi-functional projects, including defining architecture, managing technical risk, resolving ambiguity, and driving solutions through delivery and adoption.
• Strong analytical and problem-solving abilities, with the judgment to prioritize effectively, manage multiple initiatives, and adapt in a dynamic, constantly evolving environment.
• Excellent communication, organizational, and influencing skills, with the ability to align globally distributed collaborators and drive decisions.
• A record of mentoring engineers, elevating engineering quality, and helping teams make better technical decisions.

Nice to Have

• Experience leading major initiatives in GPU or AI infrastructure, distributed training or inference, model evaluation, or performance benchmarking.
• Experience architecting workflow engines, schedulers, experiment platforms, test frameworks, or developer infrastructure used by multiple teams.
• Experience operating distributed or cloud-native systems at scale, including performance profiling, capacity analysis, resource scheduling, or multi-node workloads.
• Practical experience establishing AI-agent, tool-calling, or coding-agent strategies that improved engineering workflows at team or organizational scale.
• Demonstrated success turning loosely defined, cross-organizational problems into durable platforms or programs with measurable engineering impact.

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As the complexity and scale of artificial intelligence continue to grow, the intersection of advanced deep learning architectures, massive-scale distributed computing, and low-level hardware optimization has never been more critical.

Our team is dedicated to exploring and prototyping next-generation ideas that bridge the gap between deep learning algorithms and CUDA, pushing the boundaries of what is possible on modern accelerator architectures.

Join our dynamic, research-oriented team to help unlock maximum hardware performance for emerging AI workloads.

You will be a crucial member of a highly technical group exploring uncharted territories in model optimization, custom kernel development, and cluster-scale AI systems design.

If you are passionate about the fundamentals of deep learning and thrive on squeezing every ounce of performance out of advanced computing systems from a single GPU to supercomputer clusters, we want you on our team!

Responsibilities

• Explore, research, and prototype novel systems optimizations for advanced deep learning models at the intersection of high-level DL frameworks and low-level CUDA through modeling, simulation, and silicon prototyping.
• Architect and optimize distributed computing systems that scale seamlessly from a single node to massive, cluster-scale supercomputing environments.
• Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads.
• Analyze complex hardware-software interactions to identify and resolve performance bottlenecks in both training and inference pipelines.
• Collaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and algorithms that improve accelerator compute utilization, memory bandwidth, cross-node network communication efficiency and programmability.
• Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.
• Write clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products.

Requirements

• BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
• 2+ years of relevant industry experience or equivalent academic experience after degree achievement.
• Strong proficiency in C++ and Python programming.
• Solid background in the fundamentals of Deep Learning with a focus on transformers.
• Strong understanding of distributed computing principles, multi-node scaling, and the unique performance challenges of cluster-scale execution.
• Proven experience in systems programming, computer architecture, and low-level systems performance optimization.
• Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience with CUDA programming, kernel optimization, and workload profiling.
• Experience profiling and optimizing generative AI models, including but not limited to, pioneering large language models.
• Research background in machine learning systems or adjacent fields and experience profiling and optimizing innovative vision models, generative AI architectures, or diffusion models.
• A track-record of initiative and willingness to deep-dive on problems across the stack.

Nice to Have

• Deep expertise in performance internals and execution graphs of major deep learning training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron).
• Hands-on experience with communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline, tensor, expert parallelism).
• Knowledge of numerical methods and low-precision arithmetic (e.g., NVFP4, MXFP4, FP8, INT8) and their impact on deep learning accuracy and performance.
• Background in deep learning compilers and ML systems, including graph-level and codegen tools (e.g., Triton, XLA, torch.compile) and highly parallel/RL-style simulation environments.
• Experience designing and implementing agentic AI systems applied to complex systems and infrastructure problems.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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As the complexity and scale of artificial intelligence continue to grow, the intersection of advanced deep learning architectures, massive-scale distributed computing, and low-level hardware optimization has never been more critical.

Our team is dedicated to exploring and prototyping next-generation ideas that bridge the gap between deep learning algorithms and CUDA, pushing the boundaries of what is possible on modern accelerator architectures.

Join our dynamic, research-oriented team to help unlock maximum hardware performance for emerging AI workloads.

You will be a crucial member of a highly technical group exploring uncharted territories in model optimization, custom kernel development, and cluster-scale AI systems design.

If you are passionate about the fundamentals of deep learning and thrive on squeezing every ounce of performance out of advanced computing systems from a single GPU to supercomputer clusters, we want you on our team!

Responsibilities

• Explore, research, and prototype novel systems optimizations for advanced deep learning models at the intersection of high-level DL frameworks and low-level CUDA through modeling, simulation, and silicon prototyping.
• Architect and optimize distributed computing systems that scale seamlessly from a single node to massive, cluster-scale supercomputing environments.
• Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads.
• Analyze complex hardware-software interactions to identify and resolve performance bottlenecks in both training and inference pipelines.
• Collaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and algorithms that improve accelerator compute utilization, memory bandwidth, cross-node network communication efficiency and programmability.
• Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning.
• Write clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products.

Requirements

• BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
• 8+ years of relevant industry experience or equivalent academic experience after degree achievement.
• Strong proficiency in C++ and Python programming.
• Solid background in the fundamentals of Deep Learning with a focus on transformers.
• Strong understanding of distributed computing principles, multi-node scaling, and the unique performance challenges of cluster-scale execution.
• Proven experience in systems programming, computer architecture, and low-level systems performance optimization.
• Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience with CUDA programming, kernel optimization, and workload profiling
• Experience profiling and optimizing generative AI models, including but not limited to, pioneering large language models.
• Research background in machine learning systems or adjacent fields and experience profiling and optimizing innovative vision models, generative AI architectures, or diffusion models.
• A track-record of initiative and willingness to deep-dive on problems across the stack.

Nice to Have

• Deep expertise in performance internals and execution graphs of major deep learning training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron).
• Hands-on experience with communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline, tensor, expert parallelism).
• Knowledge of numerical methods and low-precision arithmetic (e.g., NVFP4, MXFP4, FP8, INT8) and their impact on deep learning accuracy and performance.
• Background in deep learning compilers and ML systems, including graph-level and codegen tools (e.g., Triton, XLA, torch.compile) and highly parallel/RL-style simulation environments.
• Experience designing and implementing agentic AI systems applied to complex systems and infrastructure problems.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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Responsibilities

• Invent and optimize new methods for increasing chip frequency while minimizing power consumption across a suite of internal optimization tools.
• Improve algorithms (in C++) for IR drop optimization, simulation.
• Own the whole process from discovery and invention of new optimization opportunities to developing solutions and working directly inside design teams to facilitate deployment.

Requirements

• BS, MS, PhD in Electrical Engineering or Computer Science or equivalent experience.
• Minimum 2+ years of relevant experience in CAD software and VLSI hardware design.
• Strength in both CAD software and VLSI design.
• Understanding of VLSI IR drop optimization or simulation and related concepts, including constraints, corner, CCSP, FSDB etc.
• Demonstrated ability in software development using C++.
• Strong communication and interpersonal skills.

Nice to Have

• Familiarity with RedHawk and typical design flows written in Perl, Tcl, and Python.
• C++14 or newer experience, such as lambdas and concurrency.
• Experience in high-performance software design including multithreading, distributed computing, efficient memory, and I/O use, etc.
• Experience in IR drop optimization, calculation.

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

The impact you will have:

• Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
• Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications
• Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks
• Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs
• Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact
• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap

What we look for:

• 6+ years experience in data engineering, data platforms & analytics, or software engineering
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps, ML/AI models and AI APIs
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions
• Documentation and white-boarding skills
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects
• Travel to customers 20% of the time
• Databricks Certification

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

The impact you will have:

• Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration.
• Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications.
• Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
• Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models and AI APIs.
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time.
• Databricks Certification.

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations.

FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact.

The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes.

FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

The impact you will have:

• Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration.
• Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications.
• Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
• Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models and AI APIs.
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time.
• Databricks Certification.

Pay Range Transparency: The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

Zone 1 Pay Range: $182,000-$250,208 USD Zone 2 Pay Range: $182,000-$250,208 USD Zone 3 Pay Range: $182,000-$250,208 USD Zone 4 Pay Range: $182,000-$250,208 USD

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

The impact you will have:

• Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration.
• Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications.
• Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
• Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

• 5+ years experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models and AI APIs.
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time.

The pay range for this role is $152,900-$210,155 USD.

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We are seeking a Senior R&D Software Engineer with proven experience in multiple areas of VLSI Physical Design Algorithms (sizing, buffering, CTS, legalization, incremental place and route etc.). Understanding both software and hardware aspects is key. Creativity and self-drive to explore and perfect fast, high-capacity software are required.

Responsibilities:

• Invent new optimization engines that fuse traditionally independent engines (e.g., co-optimization of legalization and sizing) with the objective of increasing chip frequency while minimizing power consumption across a suite of internal optimization tools.
• Improve algorithms (in C++) for gate-level sizing, buffering, useful clock skew, cell legalization, power minimization, ECO routing, and incremental parasitic extraction.
• Own the whole process from discovery and invention of new optimization opportunities, to developing solutions and working directly inside design teams to facilitate deployment.

Requirements:

• BS, MS, PhD or equivalent experience in Electrical Engineering or Computer Science
• 6+ years in VLSI algorithms development using C++
• Strong understanding of VLSI timing optimization and related concepts, including cell libraries, interconnect models, crosstalk, glitches, IR drop, timing constraints, corners, congestion, etc.
• Familiarity with design implementation tools such as ICC2, Innovus, PrimeTime, Tempus, and StarRC and typical design flows written in Perl, Tcl, and Python
• Strong communication and interpersonal skills

Preferred Qualifications:

• C++14 or newer experience, such as lambdas and concurrency
• Detailed understanding of how multiple Physical Design steps interact and how they can potentially be fused together to form hybrid engines that result in better PPA
• Experience in high-performance software design including multithreading, distributed computing, efficient memory and I/O use, etc.
• Highly driven to craft outstanding software towards improving PPA with a dedication to continuous improvement
• Experience with reinforcement learning, GNNs (Graph Neural Networks), and other relevant machine learning frameworks, especially as applied to physical design

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Responsibilities:

In this role, you will develop innovative solutions that advance AI infrastructure capabilities. You will directly influence customer success with breakthrough AI initiatives.

• Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed on NVIDIA reference architectures.

• Act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines.

• Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds.

• Profile and tune large-scale training and inference workloads on NCP platforms. Implement observability and SLO/SLA monitoring. Lead detailed efforts to reduce latency, cost, and operational risk.

• Implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity.

• Build detailed implementation guides, runbooks, and post-mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.

Requirements:

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.

• 8+ years of experience in customer-facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting large-scale cloud or service provider environments.

• Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms.

• Demonstrated AI/ML experience supporting large-scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments.

• Solid programming skills in Python/Go, with hands-on experience using frameworks such as PyTorch or TensorFlow for training and serving.

• Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution.

• Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.

Nice to Have:

• Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and NVIDIA networking technologies such as InfiniBand and RoCE.

• Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms, including implementation of NVIDIA reference architectures for AI infrastructure.

• Deep familiarity with MLOps and cloud-native practices: containerization, CI/CD pipelines, observability stacks (Prometheus, Grafana, OpenTelemetry), and GitOps workflows.

• Background in infrastructure as code (Terraform, Ansible, or similar) for repeatable deployment and configuration of GPU-accelerated clusters and NCP building blocks.

NVIDIA offers competitive salaries and a generous benefits package.

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As a high-performance system architect at NVIDIA, you will have the opportunity to work on some of the most cutting-edge technology and help drive the innovation of their next-generation networks that will be used by top researchers and engineers around the world.

Responsibilities:

• Define the NVL system architecture end-to-end, by internal requirements and customer requirements through all product life cycles.
• Research various solutions to enable the next large-scale high-performance computing clusters.
• Collaborate with cross-functional teams to ensure the successful execution of the project.

Requirements:

• B.Sc, M.Sc, or Ph.D degree in Computer Science, Computer Engineer, or Electrical Engineer.
• At least 5 years of industry or research experience in computer networks.
• Excellent understanding of large-scale networks behavior and the effect of distributed computing workloads on the network.
• Experience in developing models for simulations, analyzing simulation results, and development of optimization algorithms.
• Possess strong managerial, problem-solving, and critical thinking skills.
• Ability to work and operate in a highly dynamic environment.

Preferred Qualifications:

• Good knowledge in network protocols - such as InfiniBand, IP, TCP, and RoCE and network topologies.
• Good knowledge in Python, C++.
• Familiarity with HPC environments, routing algorithms, Omnet++, and NS3 simulation environments.

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You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.

Your responsibilities will include:

• Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications, and data ingestion and ML/AI model integration.
• Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end-to-end design, build, and deployment of industry-leading big data and AI applications.
• Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which lead to a customer's successful understanding, evaluation, and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Collaborate with the Databricks technical team, Project Manager, Architect, and Customer team to ensure the technical components of the engagement are delivered to meet the customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues.
• Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Requirements:

• 6+ years of experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models, and AI APIs.
• Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
• Experience with technical project delivery - managing scope, timelines, and measurable outcomes, translating complex concepts into actionable solutions.
• Documentation and white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time.
• Databricks Certification.

We offer comprehensive benefits and perks that meet the needs of all our employees.

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You will cultivate, guide, and scale a dynamic organization focused on enterprise software, big data, healthcare interoperability (e.g., FHIR/HL7), clinical/claims analytics, real-world evidence (RWE), and medical AI/ML applications.

Leading this specialized pre-sales engine, you will partner closely with Sales leadership to drive consumption, maximize ARR, and help healthcare providers, payers, and pharmaceutical organizations achieve transformational business and patient outcomes.

The Impact You Will Have:

• Hire, train, and develop a high-performing tier of both individual contributors (IC) and frontline managers/leads within the Specialist Solutions Architecture organization.
• Maintain a robust, diverse hiring pipeline attuned to deep technical expertise, clinical data structures, and life sciences domain proficiency.
• Exceed regional sales and consumption targets by ensuring your management and SA teams rigorously qualify accounts, identify high-value genomic, clinical, or operational use cases, execute secure proof-of-concepts, and serve as trusted advisors across the customer lifecycle.
• Drive deep adoption of the Databricks Data Intelligence Platform, ensuring compliance frameworks (HIPAA, HITRUST, GxP) are properly mapped to outsized business and regulatory value.
• Establish strong matrixed relationships across Product Management, Engineering, Industry Solutions, and Sales to remove blockers and accelerate go-to-market velocity.

What We Look For:

• 5+ years of leadership experience directly managing technical pre-sales teams, with a proven track record of leading both high-level individual contributors (L6+) and frontline technical managers/pod leads.
• 5+ years of deep experience in the data and AI space with highly technical platforms (e.g., distributed computing, cloud data warehousing, MLOps, or generative AI infrastructure).
• Comprehensive understanding of the Healthcare and Life Sciences vertical, including hands-on familiarity with industry data models (OMOP, FHIR), regulatory constraints (HIPAA, GxP), and standard enterprise data integration/transformation patterns.
• Proven capability as a trusted strategic advisor to HLS technical executives (CTOs, CIOs, Chief Data Officers) guiding large-scale cloud infrastructure and AI roadmap decisions.
• Elite command of technical qualification methodologies, architecture design validation, structured proof-of-concept (POC) management, and value-selling frameworks.
• Demonstrated history of organizational scaling,successfully hiring complex profiles, accelerating onboarding cycles, coaching leaders, and managing progression pathways.
• Strong operational rigor around pipeline tracking, resource allocation, and building cross-functional alignment between Field Engineering, Sales, and Customer Success.

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Zone 2 Pay Range $219,600-$301,875 USD

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You will deliver hands-on technical assistance for advanced AI deployments, intricate distributed systems, and ensure customers realize efficient performance from NVIDIA's AI platform across varied environments.

Responsibilities

• Develop innovative solutions that advance AI infrastructure capabilities.
• Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed on NVIDIA reference architectures.
• Act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines.
• Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds.
• Profile and tune large-scale training and inference workloads on NCP platforms.
• Implement observability and SLO/SLA monitoring.
• Lead detailed efforts to reduce latency, cost, and operational risk.
• Implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity.
• Build detailed implementation guides, runbooks, and post-mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.

Requirements

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
• 8+ years of experience in customer-facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting large-scale cloud or service provider environments.
• Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms.
• Demonstrated AI/ML experience supporting large-scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments.
• Solid programming skills in Python/Go, with hands-on experience using frameworks such as PyTorch or TensorFlow for training and serving.
• Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution.
• Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.

Nice to Have

• Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and NVIDIA networking technologies such as InfiniBand and RoCE.
• Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms, including implementation of NVIDIA reference architectures for AI infrastructure.
• Deep familiarity with MLOps and cloud-native practices: containerization, CI/CD pipelines, observability stacks (Prometheus, Grafana, OpenTelemetry), and GitOps workflows.
• Background in infrastructure as code (Terraform, Ansible, or similar) for repeatable deployment and configuration of GPU-accelerated clusters and NCP building blocks.

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Join Temporal Technologies as a Senior Application Security Engineer, playing a crucial role in securing the company's development pipeline, product, and customer execution environment. You will collaborate with software engineering teams and customers to integrate security into the platform across multiple clouds.

Responsibilities

• Collaborate with product and engineering teams to integrate security principles into product design and architecture.
• Conduct threat modeling and risk assessments to identify vulnerabilities and potential attack vectors.
• Manage the Secure Development pipeline, including code security and third-party library supply chain security.
• Stay updated on emerging standards and translate them into actionable internal policies.
• Triage Bug Bounty findings and responsibly disclosed vulnerabilities.
• Participate in on-call rotations.

Requirements

• Bachelor's degree in Computer Science, Cybersecurity, or a related field (or equivalent experience).
• 5+ years of experience in application or product security.
• Proven ability to partner with engineering teams, bringing security expertise to the planning and development process.
• Knowledge of encryption, authentication, and secure communication protocols.
• Familiarity with tools like SAST, DAST, and penetration testing frameworks.
• Deep understanding of application architecture and design principles.
• Excellent communication skills, with the ability to explain complex security concepts to non-technical stakeholders.
• Experience with Kubernetes security posture management and auditing.
• Demonstrated experience with multi-tenant security architecture.
• Expertise in at least one programming language, with familiarity with Python and Go.

Nice to Have

• Distributed computing and related vulnerability experience.
• Experience running a Security Champions program.
• Involvement in open-source automation or automation projects.
• Expertise in other areas of security.
• Security conference talks or published research.

Compensation

• Estimated pay range: $180,000 - $225,000, depending on qualifications and location.
• Eligible to participate in Temporal's equity plan.

Benefits

• Unlimited PTO, 12 holidays + 2 floating holidays.
• 100% premiums coverage for medical, dental, and vision.
• AD&D, LT & ST disability, and life insurance.
• Empower 401K plan.
• Additional perks for learning & development, lifestyle spending, in-home office setup, professional memberships, WFH meals, internet stipend, and more.

Travel

• Occasional travel may be required for company events, team offsites, and other meaningful moments.

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In this hands-on, builder-focused engineering role, you will bridge Product, Design, and Engineering to develop, evaluate, and maintain scalable, low-latency, ML-based systems for real-time applications. You will lead rapid research-to-production cycles that translate business ideas into solutions for complex problems, such as streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks.

Responsibilities:

• Partner with product, UX, and technical stakeholders to analyze business problems and define measurable ML problem statements.
• Design, implement, and maintain scalable, enterprise-grade ML solutions in production.
• Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling.
• Implement monitoring and evaluation frameworks to continuously improve data quality, model performance, latency, and cost.
• Collaborate cross-functionally with Product, Data Science/ML, Engineering, and Security to deliver resilient, scalable, and compliant ML-powered services.
• Demonstrate end-to-end systems understanding and articulate the 'why' behind model and system design choices.
• Own operational excellence, including SLAs, on-call, incident response, and customer feedback triage.
• Drive engineering excellence via AI-assisted SDLC, code reviews, automated testing, MLOps best practices, knowledge-sharing, and mentoring.

Qualifications:

• Strong foundation in ML/AI with 5+ years of experience building, deploying, and operating data and ML systems in production.
• Proficient in Python, Java, and SQL with strong software engineering fundamentals.
• Hands-on experience with workflow orchestration, data pipelines, cloud data platforms/storage, and MLOps tooling.
• Working knowledge of containerization, cloud infrastructure, and distributed computing.

Location: Remote - US (not eligible to be hired in CA, CT, NJ, NY, PA, WA)

Travel: Occasional travel required for project or team in-person meetings

Compensation: Estimated pay ranges vary by location

• Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont, or Washington D.C.: $155,520 - $194,400
• New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $164,640 - $205,800
• San Francisco Bay area, California: $182,960 - $228,700

Benefits: Competitive pay, generous time off, parental and wellness leave, healthcare, retirement savings program, and more

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The Lakeflow Engineering team owns the entirety of the ETL product line: Declarative Dataflow Graphs, Materialised Views, Structured Streaming, and Flows. We run what is arguably the world's largest data engineering platform, processing exabytes of data daily across tens of thousands of customers. The problems we solve (fault-tolerant incremental computation, stream-batch unification, declarative pipeline orchestration at massive scale) sit at the frontier of what distributed data systems can do.

We're looking for a Senior Staff Engineer to serve as a technical architect and engineering leader for this platform. You'll own the long-term technical direction for how pipelines are defined, optimised, executed, and operated, shaping the systems that data teams worldwide depend on every day. You will work across one or more of the following areas to design and build the next generation of data infrastructure:

• Declarative Dataflow Processing
• Resource management
• Efficient storage structures
• Stream Processing and Complex Event Processing
• Autonomic Computing and Self-Managing Systems

The Impact you will have:

• Architect and deliver a highly scalable, fault-tolerant platform for declarative pipelines and materialised views serving thousands of production customers.
• Turn ambiguous, large-scale technical challenges into clear execution plans that ship incrementally and hold up at exabyte scale.
• Bridge the gap between research and production by bringing ideas from the academic literature or internal R&D into systems that solve real customer problems.
• Lead deep systems work: performance diagnosis on large production clusters, low-level debugging, and optimisation that moves the needle on cost and latency.
• Shape product direction alongside engineering and product leadership, owning technical strategy from design through delivery.
• Drive complex, multi-team technical initiatives that require sustained coordination and clear technical judgment.

What We’re Looking For:

• 10+ years of experience building, operating, and evolving large-scale distributed systems in production.
• Deep expertise in one or more of: database internals, storage systems, distributed computing, streaming systems, language/API design, or performance engineering.
• Track record of executing against a multi-year technical vision through well-sequenced incremental milestones.
• Strong algorithmic foundations with the practical judgment to know when they matter and when simpler solutions win.
• A bias toward customer impact over technical novelty for its own sake.
• Experience building alignment across teams and driving initiatives from conception through customer adoption.
• BS, MS, or PhD in Computer Science or a related field (or equivalent depth of experience).

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilising the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range $228,600-$314,250 USD

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As a Staff Robotics Software Engineer on our Tactical Recon & Strike (TRS) team, you'll be at the forefront of cutting-edge autonomous systems development.

Responsibilities

• Develop and maintain core robotics libraries, including frame transformations, targeting, and guidance systems, that will be utilized across all Anduril robotics platforms.
• Lead the development and implementation of major features for our products, such as designing and building Software-in-the-Loop simulators for advanced systems like Anvil.
• Optimize performance of existing products, including tasks like improving battery consumption and route planning for our Ghost helicopter.
• Collaborate closely with hardware and manufacturing teams throughout the product development lifecycle, providing timely feedback to influence and enhance final hardware designs.
• Troubleshoot and resolve complex issues in deployed systems, ensuring optimal performance in the field.
• Contribute to the design and implementation of multi-agent coordination systems for UAVs.
• Participate in the full software development lifecycle, from concept and design through testing and deployment.
• Stay current with emerging technologies and industry trends, recommending and implementing innovations to improve our products and processes.

Requirements

• Bachelor's degree in Robotics, Computer Science, or related field.
• 7+ years of professional software development experience.
• Strong proficiency in C++ or Rust, with experience in Linux development environments.
• Demonstrated expertise in data structures, algorithms, concurrency, and code optimization.
• Proven experience troubleshooting and analyzing remotely deployed software systems.
• Hands-on experience working with and testing electrical and mechanical systems.
• Ability to collaborate effectively with cross-functional teams, including hardware and manufacturing.
• Strong problem-solving skills and a "Whatever It Takes" mindset.
• Excellent communication skills, both written and verbal.
• Eligible to obtain and maintain an active U.S. Secret security clearance.
• Willingness to relocate to Costa Mesa, CA.

Preferred Qualifications

• Master's or Ph.D. in a relevant field (e.g., Robotics, Computer Science, Electrical Engineering).
• Expertise in one or more advanced robotics areas: motion planning, perception, localization, mapping, or controls.
• Experience with performance optimization and metrics for complex robotic systems.
• Proficiency in Python, Rust, and/or Go, in addition to C++.
• Hands-on experience programming for embedded systems and physical devices.
• Background in multi-agent coordination, particularly with UAVs.
• Demonstrated ability to solve complex frame transformation problems (e.g., target localization, multi-degree-of-freedom robotic arms).
• Experience with real-time operating systems and distributed computing.
• Familiarity with machine learning and AI applications in robotics.
• Knowledge of sensor fusion techniques and implementation.
• Understanding of aerodynamics and flight dynamics as applied to UAV systems.
• Experience with simulation environments for robotics testing and development.
• Track record of contributions to open-source robotics projects or relevant publications.

Benefits

• Comprehensive medical, dental, and vision plans.
• Income protection: life and disability insurance.
• Generous time off: highly competitive PTO plans.
• Family planning and parenting support.
• Mental health resources.
• Professional development: annual reimbursement.
• Commuter benefits.
• Relocation assistance.
• Retirement savings plan.

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You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers get the most value out of their data.

Responsibilities:

• Work on various impactful customer technical projects, designing and building reference architectures, creating how-to's, and productionalizing customer use cases
• Collaborate with engagement managers to scope professional services work with input from customers
• Guide strategic customers in implementing transformational big data projects, 3rd party migrations, and end-to-end design, build, and deployment of industry-leading big data and AI applications
• Consult on architecture and design, bootstrap or implement customer projects, and provide escalated support for customer operational issues
• Work with the Databricks technical team, Project Manager, Architect, and Customer team to deliver technical components of engagements
• Provide product and implementation feedback and guide rapid resolution for engagement-specific product and support issues

Requirements:

• 6+ years of experience in data engineering, data platforms, and analytics
• Proficiency in writing code in Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments, MLOps, and design and deployment of performant end-to-end data architectures
• Experience with technical project delivery, managing scope and timelines, documentation, and white-boarding skills
• Ability to travel to customers 20% of the time
• Databricks Certification

Pay Range: $180,656 - $248,360 USD

Benefits: Comprehensive benefits and perks that meet the needs of all employees.

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers get the most value out of their data.

Responsibilities:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's, and productionalizing customer use cases
• Collaborate with engagement managers to scope professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build, and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which lead to a customer's successful understanding, evaluation, and adoption of Databricks
• Provide an escalated level of support for customer operational issues
• Work with the Databricks technical team, Project Manager, Architect, and Customer team to ensure the technical components of the engagement are delivered to meet the customer's needs
• Collaborate with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues

Requirements:

• 6+ years of experience in data engineering, data platforms, and analytics
• Proficiency in writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines
• Documentation and white-boarding skills
• Experience working with clients and managing conflicts
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects
• Travel to customers 20% of the time
• Databricks Certification

Pay Range: $180,656 - $248,360 USD

XML job scraping automation by YubHub

Your role will be pivotal in ensuring Anduril's products work seamlessly together to achieve a variety of crucial outcomes. You will develop innovative solutions for complex robotics problems, balance pragmatic engineering trade-offs with mission-critical requirements, and collaborate across teams to integrate software with hardware systems. Contributing to the entire product lifecycle, from concept to deployment, you will rapidly prototype and iterate on software solutions. We're looking for someone who thrives in a fast-paced environment and isn't afraid to tackle ambiguous problems. Your 'Whatever It Takes' mindset will be key in executing tasks efficiently, scalably, and pragmatically, always keeping the mission at the forefront of your work. This role offers the opportunity to make a significant impact on next-generation defence technology, working with state-of-the-art robotics and autonomous systems. You will be part of a team that values innovation, quick iteration, and delivering high-quality solutions that meet real-world needs.

Must be eligible to obtain and maintain an active U.S. Secret security clearance. This position will be located at our headquarters in Costa Mesa, CA (relocation benefits provided.)

Key Responsibilities:

• Develop and maintain core robotics libraries, including frame transformations, targeting, and guidance systems, that will be utilised across all Anduril robotics platforms
• Lead the development and implementation of major features for our products, such as designing and building Software-in-the-Loop simulators for advanced systems like Anvil
• Optimise performance of existing products, including tasks like improving battery consumption and route planning for our Ghost helicopter
• Collaborate closely with hardware and manufacturing teams throughout the product development lifecycle, providing timely feedback to influence and enhance final hardware designs
• Troubleshoot and resolve complex issues in deployed systems, ensuring optimal performance in the field
• Contribute to the design and implementation of multi-agent coordination systems for UAVs
• Participate in the full software development lifecycle, from concept and design through testing and deployment
• Stay current with emerging technologies and industry trends, recommending and implementing innovations to improve our products and processes

XML job scraping automation by YubHub

Your role will be pivotal in ensuring Anduril's products work seamlessly together to achieve a variety of crucial outcomes. You will develop innovative solutions for complex robotics problems, balance pragmatic engineering trade-offs with mission-critical requirements, and collaborate across teams to integrate software with hardware systems. Contributing to the entire product lifecycle, from concept to deployment, you will rapidly prototype and iterate on software solutions.

We are looking for someone who thrives in a fast-paced environment and isn't afraid to tackle ambiguous problems. Your 'Whatever It Takes' mindset will be key in executing tasks efficiently, scalably, and pragmatically, always keeping the mission at the forefront of your work.

This role offers the opportunity to make a significant impact on next-generation defence technology, working with state-of-the-art robotics and autonomous systems. You will be part of a team that values innovation, quick iteration, and delivering high-quality solutions that meet real-world needs.

The successful candidate will have a Bachelor's degree in Robotics, Computer Science, or a related field, and at least 5 years of professional software development experience. They will be proficient in C++ or Rust, with experience in Linux development environments, and have demonstrated expertise in data structures, algorithms, concurrency, and code optimisation. The ideal candidate will also have hands-on experience working with and testing electrical and mechanical systems, and be able to collaborate effectively with cross-functional teams.

Responsibilities:

Develop and maintain core robotics libraries, including frame transformations, targeting, and guidance systems, that will be utilised across all Anduril robotics platforms.

Lead the development and implementation of major features for our products, such as designing and building an end-to-end target tracking pipeline for Dart.

Collaborate closely with hardware and manufacturing teams throughout the product development lifecycle, providing timely feedback to influence and enhance final hardware designs.

Troubleshoot and resolve complex issues in deployed systems, ensuring optimal performance in the field.

Participate in the full software development lifecycle, from concept and design through testing and deployment.

Stay current with emerging technologies and industry trends, recommending and implementing innovations to improve our products and processes.

Required Qualifications:

Bachelor's degree in Robotics, Computer Science, or related field

5+ years of professional software development experience

Strong proficiency in C++ or Rust, with experience in Linux development environments

Demonstrated expertise in data structures, algorithms, concurrency, and code optimisation

Proven experience troubleshooting and analysing remotely deployed software systems

Hands-on experience working with and testing electrical and mechanical systems

Ability to collaborate effectively with cross-functional teams, including hardware and manufacturing

Strong problem-solving skills and a 'Whatever It Takes' mindset

Excellent communication skills, both written and verbal

Eligible to obtain and maintain an active U.S. Secret security clearance

Willingness to relocate to Costa Mesa, CA

Preferred Qualifications:

Master's or Ph.D. in a relevant field (e.g., Robotics, Computer Science, Electrical Engineering)

Expertise in one or more advanced robotics areas: motion planning, perception, localisation, mapping, or controls

Experience with performance optimisation and metrics for complex robotic systems

Proficiency in Python, Rust, and/or Go, in addition to C++

Hands-on experience programming for embedded systems and physical devices

Background in multi-agent coordination, particularly with UAVs

Demonstrated ability to solve complex frame transformation problems (e.g., target localisation, multi-degree-of-freedom robotic arms)

Experience with real-time operating systems and distributed computing

Familiarity with machine learning and AI applications in robotics

Knowledge of sensor fusion techniques and implementation

Understanding of aerodynamics and flight dynamics as applied to UAV systems

Experience with simulation environments for robotics testing and development

Track record of contributions to open-source robotics projects or relevant publications

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In this role, you will be responsible for inventing new methods to enable parallel, graph-based RTL traversal, analysis, and manipulation. You will also devise strategies for rapidly analyzing the impact of RTL changes on data path latency, power, and impact to DFT, clocking, and power delivery.

Requirements:

• MS or PhD in Electrical Engineering or Computer Science or equivalent experience
• 3+ years of relevant experience in CAD software and VLSI hardware design
• Demonstrated ability in software development with C++, particularly in algorithm development related to graph traversal, pattern matching, and optimization
• Familiarity with RTL design, including Verilog and SystemVerilog code, as well as general hardware design concerns such as scan chain insertion, MBIST, clock and power distribution, and bus architectures
• Familiarity with related EDA techniques, including logic synthesis, global route, static timing analysis, and SAT solvers
• Strong communication and interpersonal skills

Preferred qualifications include experience with common EDA building blocks, such as Verific for Verilog parsing, Espresso for logic minimization, and various other components for logic rewriting, tree coverage, SAT solvers, and combinatorial optimization. Experience in high performance software design including multithreading, distributed computing, efficient memory and I/O use, etc. is also desired.

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Developing software within a leading hardware company means getting to almost exclusively focus on the latest processes and most advanced designs. We're not bogged down by legacy support, niche roles, or convoluted approval processes. Our developers enjoy unusually high intellectual freedom and the ability to explore broad roles.

Responsibilities:

• Invent new optimization engines that fuse traditionally independent engines (e.g., co-optimization of legalization and sizing) with the objective of increasing chip frequency while minimizing power consumption across a suite of internal optimization tools.

• Improve algorithms (in C++) for gate-level sizing, buffering, useful clock skew, cell legalization, power minimization, ECO routing, and incremental parasitic extraction.

• We as a team own the whole process from discovery and invention of new optimization opportunities, to developing solutions and working directly inside design teams to facilitate deployment.

Requirements:

• Masters or PhD in Electrical Engineer or Computer Science (or equivalent experience).

• Experience with VLSI algorithms development using C++.

• Understanding of VLSI timing optimization and related concepts, including cell libraries, interconnect models, crosstalk, glitches, IR drop, timing constraints, corners, congestion, etc.

• Familiarity with design implementation tools such as ICC2, Innovus, PrimeTime, Tempus, and StarRC and typical design flows written in Perl, Tcl, and Python.

Nice to Have:

• C++14 or newer experience, such as lambdas and concurrency.

• Understanding of how multiple Physical Design steps interact and how they can potentially be fused together to form hybrid engines that result in better PPA.

• Experience in high performance software design including multithreading, distributed computing, efficient memory and I/O use, etc.

• Highly driven to craft software towards improving PPA with a dedication to continuous improvement.

• Experience with reinforcement learning, GNNs (Graph Neural Networks), and other relevant machine learning frameworks, especially as applied to physical design.

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This is a hands-on, builder-focused engineering role that bridges Product, Design, and Engineering to develop, evaluate, and maintain scalable, low-latency, ML-based systems for real-time applications. You will lead rapid research-to-production cycles that translate business ideas into solutions for complex problems,such as streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks,with the goal of delivering personalized customer experiences.

In this role, you'll:

Partner with product, UX, and technical stakeholders to analyze business problems, clarify requirements, define scope, and translate them into measurable ML problem statements.

Design, implement, and maintain scalable, enterprise-grade ML solutions in production.

Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling.

Implement monitoring and evaluation frameworks to continuously improve data quality, model performance, latency, and cost through feedback loops.

Partner cross-functionally with Product, Data Science/ML, Engineering, and Security to deliver resilient, scalable, and compliant ML-powered services.

Demonstrate end-to-end systems understanding and articulate the 'why' behind model and system design choices.

Own operational excellence: SLAs, on-call, incident response, customer feedback triage, and blameless post-mortems.

Drive engineering excellence via AI-assisted SDLC, code reviews, automated testing, MLOps best practices, knowledge-sharing, and mentoring.

Actively adopt AI-assisted practices to improve implementation and collaboration efficiency.

Qualifications:

Strong foundation in ML/AI (statistics, probability, optimization) with the ability to apply these concepts to real-world problems.

5+ years of experience building, deploying, and operating data and ML systems in production.

Proficient in Python, Java, and SQL; strong software engineering fundamentals (system design, testing, version control, code reviews).

Hands-on experience with workflow orchestration and data pipelines (e.g., Airflow, Kubeflow) and cloud data platforms/storage (e.g., SageMaker Feature Store, Snowflake, DynamoDB, OpenSearch).

Experience with the ML lifecycle and MLOps tooling (e.g., MLflow, Metaflow, SageMaker; LLM/agent frameworks such as LangChain/LangGraph; model evaluation/observability tools such as Galileo or similar).

Working knowledge of containerization and cloud infrastructure, including Docker and Kubernetes, GitOps/CI/CD tools (e.g., Argo CD), and at least one major cloud platform (AWS, GCP, or Azure).

Understanding of data modeling and scalable systems, including distributed computing and streaming frameworks (e.g., Spark/EMR, Flink, Kafka Streams); familiarity with GPU-based implementation is a plus.

Demonstrated ability to ramp up quickly and operate effectively in new application/business domains.

Strong written and verbal communication skills: able to document and present designs and decisions, and comfortable giving/receiving feedback in an Agile environment.

Desired:

Familiarity with ML problem areas and techniques, including recommendation systems (e.g., graph-based approaches, two-tower models), time-series modeling (classical and deep learning), representation learning (e.g., embeddings), anomaly detection, and causal inference.

Practical experience with LLMs and generative AI workflows, including foundation model fine-tuning, RAG, and vector databases.

Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research.

Domain experience (plus) in communications, marketing automation, or customer engagement analytics.

Familiarity with AI-assisted development tools (e.g., Claude, GitHub Copilot/Codex, Cursor, etc.).

Advanced degree preferred (M.S. or Ph.D.) in a relevant field.

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You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

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You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

The impact you will have:

• Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases

• Work with engagement managers to scope variety of professional services work with input from the customer

• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications

• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.

• Provide an escalated level of support for customer operational issues

• Collaborate with the Databricks Technical, Project Manager, Architect and Customer teams to ensure the technical components of the engagement are delivered to meet customer's needs

• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues

What we look for:

• 6+ years experience in data engineering, data platforms & analytics

• Comfortable writing code in either Python or Scala

• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one

• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals

• Familiarity with CI/CD for production deployments

• Working knowledge of MLOps

• Design and deployment of performant end-to-end data architectures

• Experience with technical project delivery - managing scope and timelines

• Documentation and white-boarding skills

• Experience working with clients and managing conflicts

• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects

• Ability to travel up to 30% when needed

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

Your role will be pivotal in ensuring Anduril's products work seamlessly together to achieve a variety of crucial outcomes. You'll develop innovative solutions for complex robotics problems, balance pragmatic engineering trade-offs with mission-critical requirements, and collaborate across teams to integrate software with hardware systems.

Contributing to the entire product lifecycle, from concept to deployment, you'll rapidly prototype and iterate on software solutions. We're looking for someone who thrives in a fast-paced environment and isn't afraid to tackle ambiguous problems. Your 'Whatever It Takes' mindset will be key in executing tasks efficiently, scalably, and pragmatically, always keeping the mission at the forefront of your work.

This role offers the opportunity to make a significant impact on next-generation defence technology, working with state-of-the-art robotics and autonomous systems. You'll be part of a team that values innovation, quick iteration, and delivering high-quality solutions that meet real-world needs.

Must be eligible to obtain and maintain an active U.S. Secret security clearance. This position will be located at our office in Atlanta, GA (relocation benefits provided.)

Key Responsibilities:

• Develop and maintain core robotics libraries, including frame transformations, targeting, and guidance systems, that will be utilized across all Anduril robotics platforms

• Lead the development and implementation of major features for our products, such as designing and building Software-in-the-Loop simulators for advanced systems like Altius

• Optimise performance of existing products, primarily focused on our Altius Drone product line

• Collaborate closely with hardware and manufacturing teams throughout the product development lifecycle, providing timely feedback to influence and enhance final hardware designs

• Troubleshoot and resolve complex issues in deployed systems, ensuring optimal performance in the field

• Contribute to the design and implementation of multi-agent coordination systems for UAVs

• Participate in the full software development lifecycle, from concept and design through testing and deployment

• Stay current with emerging technologies and industry trends, recommending and implementing innovations to improve our products and processes

Required Qualifications:

• Bachelor's degree in Robotics, Computer Science, or related field

• 3+ years of professional software development experience

• Strong proficiency in C++ or Rust, with experience in Linux development environments

• Demonstrated expertise in data structures, algorithms, concurrency, and code optimisation

• Proven experience troubleshooting and analysing remotely deployed software systems

• Hands-on experience working with and testing electrical and mechanical systems

• Ability to collaborate effectively with cross-functional teams, including hardware and manufacturing

• Strong problem-solving skills and a 'Whatever It Takes' mindset

• Excellent communication skills, both written and verbal

• Eligible to obtain and maintain an active U.S. Secret security clearance

• Willingness to relocate to Atlanta, GA

Preferred Qualifications:

• Master's or Ph.D. in a relevant field (e.g., Robotics, Computer Science, Electrical Engineering)

• Expertise in one or more advanced robotics areas: motion planning, perception, localisation, mapping, or controls

• Experience with performance optimisation and metrics for complex robotic systems

• Proficiency in Python, Rust, and/or Go, in addition to C++

• Hands-on experience programming for embedded systems and physical devices

• Background in multi-agent coordination, particularly with UAVs

• Demonstrated ability to solve complex frame transformation problems (e.g., target localisation, multi-degree-of-freedom robotic arms)

• Experience with real-time operating systems and distributed computing

• Familiarity with machine learning and AI applications in robotics

• Knowledge of sensor fusion techniques and implementation

• Understanding of aerodynamics and flight dynamics as applied to UAV systems

• Experience with simulation environments for robotics testing and development

• Track record of contributions to open-source robotics projects or relevant publications

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases

• Work with engagement managers to scope variety of professional services work with input from the customer

• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications

• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.

• Provide an escalated level of support for customer operational issues.

• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.

• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics

• Comfortable writing code in either Python or Scala

• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one

• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals

• Familiarity with CI/CD for production deployments

• Working knowledge of MLOps

• Design and deployment of performant end-to-end data architectures

• Experience with technical project delivery - managing scope and timelines.

• Documentation and white-boarding skills.

• Experience working with clients and managing conflicts.

• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.

• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

The impact you will have:

• Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases

• Work with engagement managers to scope variety of professional services work with input from the customer

• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications

• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.

• Provide an escalated level of support for customer operational issues

• Collaborate with the Databricks Technical, Project Manager, Architect and Customer teams to ensure the technical components of the engagement are delivered to meet customer's needs

• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues

You will report to the regional Manager/Lead.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics

• Comfortable writing code in either Python or Scala

• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one

• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals

• Familiarity with CI/CD for production deployments

• Working knowledge of MLOps

• Design and deployment of performant end-to-end data architectures

• Experience with technical project delivery - managing scope and timelines

• Documentation and white-boarding skills

• Experience working with clients and managing conflicts

• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects

• Ability to travel up to 30% when needed

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

We conduct all interviews in Python, and this role may require responding to incidents on short-notice, including on weekends.

Responsibilities:

Implement and optimize post-training techniques at scale on frontier models

Conduct research to develop and optimize post-training recipes that directly improve production model quality

Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation

Develop tools to measure and improve model performance across various dimensions

Collaborate with research teams to translate emerging techniques into production-ready implementations

Debug complex issues in training pipelines and model behavior

Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

Thrive in controlled chaos and are energized, rather than overwhelmed, when juggling multiple urgent priorities

Adapt quickly to changing priorities

Maintain clarity when debugging complex, time-sensitive issues

Have strong software engineering skills with experience building complex ML systems

Are comfortable working with large-scale distributed systems and high-performance computing

Have experience with training, fine-tuning, or evaluating large language models

Can balance research exploration with engineering rigor and operational reliability

Are adept at analyzing and debugging model training processes

Enjoy collaborating across research and engineering disciplines

Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

Have experience with LLMs

Have a keen interest in AI safety and responsible deployment

We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems.

However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.

The annual compensation range for this role is $350,000-$500,000 USD.

XML job scraping automation by YubHub

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the role

Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

Responsibilities

• Implement and optimize post-training techniques at scale on frontier models
• Conduct research to develop and optimize post-training recipes that directly improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations
• Debug complex issues in training pipelines and model behavior
• Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
• Adapt quickly to changing priorities
• Maintain clarity when debugging complex, time-sensitive issues
• Have strong software engineering skills with experience building complex ML systems
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Can balance research exploration with engineering rigor and operational reliability
• Are adept at analyzing and debugging model training processes
• Enjoy collaborating across research and engineering disciplines
• Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

• Have experience with LLMs
• Have a keen interest in AI safety and responsible deployment

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links,visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

XML job scraping automation by YubHub

You will work on a variety of impactful customer technical projects, including designing and building reference architectures, creating how-to's and productionalizing customer use cases. You will also work with engagement managers to scope professional services work with input from the customer, guide strategic customers as they implement transformational big data projects, and consult on architecture and design.

To be successful in this role, you will need to have 6+ years of experience in data engineering, data platforms, and analytics, be comfortable writing code in either Python or Scala, and have working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one. You should also have deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.

The pay range for this role is $180,656-$248,360 USD, and the total compensation package may also include eligibility for annual performance bonus, equity, and benefits.

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

XML job scraping automation by YubHub

You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data.

RSAs are billable and know how to complete projects according to specification with excellent customer service.

You will report to the regional Manager/Lead.

The impact you will have:

• Work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time

Databricks Certification

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipated utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $180,656-$248,360 USD

Zone 2 Pay Range $180,656-$248,360 USD

Zone 3 Pay Range $180,656-$248,360 USD

Zone 4 Pay Range $180,656-$248,360 USD

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Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

_Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends._

Responsibilities:

• Implement and optimize post-training techniques at scale on frontier models
• Conduct research to develop and optimize post-training recipes that directly improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations
• Debug complex issues in training pipelines and model behavior
• Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
• Adapt quickly to changing priorities
• Maintain clarity when debugging complex, time-sensitive issues
• Have strong software engineering skills with experience building complex ML systems
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Can balance research exploration with engineering rigor and operational reliability
• Are adept at analysing and debugging model training processes
• Enjoy collaborating across research and engineering disciplines
• Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

• Have experience with LLMs
• Have a keen interest in AI safety and responsible deployment

We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$350,000 - $500,000USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

XML job scraping automation by YubHub

Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

_Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends._

Responsibilities:

• Implement and optimize post-training techniques at scale on frontier models

• Conduct research to develop and optimize post-training recipes that directly improve production model quality

• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation

• Develop tools to measure and improve model performance across various dimensions

• Collaborate with research teams to translate emerging techniques into production-ready implementations

• Debug complex issues in training pipelines and model behavior

• Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities

• Adapt quickly to changing priorities

• Maintain clarity when debugging complex, time-sensitive issues

• Have strong software engineering skills with experience building complex ML systems

• Are comfortable working with large-scale distributed systems and high-performance computing

• Have experience with training, fine-tuning, or evaluating large language models

• Can balance research exploration with engineering rigor and operational reliability

• Are adept at analyzing and debugging model training processes

• Enjoy collaborating across research and engineering disciplines

• Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

• Have experience with LLMs

• Have a keen interest in AI safety and responsible deployment

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

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