In this role, you will be responsible for shaping multi-year technical strategy, driving architectural coherence across organisations, and building systems that serve as foundational platforms for multiple product surfaces. You will lead the design and evolution of distributed backend systems, cloud-native infrastructure, and data platforms that operate at global scale with strict requirements for availability, latency, security, and cost efficiency.

These systems form the backbone for intelligent user experiences and must be designed for long-term extensibility and operational excellence. Building on this foundation, you will guide the integration of LLM-powered capabilities into production systems,defining patterns for retrieval, orchestration, evaluation, and responsible AI. You will ensure these capabilities are not isolated features, but deeply embedded, reliable, and scalable parts of the platform.

This role requires exceptional technical judgment, the ability to operate in highly ambiguous spaces, and a track record of influencing across teams and organisations. You will work closely with engineering leaders, product leaders, and applied scientists to align technical investments with long-term business outcomes.

Microsoft’s mission is to empower every person and every organisation on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals. Each day, we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

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We are looking for world-class Software Engineers to join our core Backend Engineering teams. You will design, build, and scale the distributed systems that power one of the largest data and AI infrastructures in the world. You will tackle high-scale infrastructure challenges where 'zero-waste' compute efficiency and 100% system resilience are mandatory. From optimising massive data storage layers to architecting low-latency microservices that must function in disconnected regions, you will own the end-to-end lifecycle of mission-critical code.

Key responsibilities include:

• Architecting scalable systems using Scala, Java, Go, C++/C or similar
• Designing and implementing highly available backend services in Java, Scala, or Go that power our Data Intelligence Platform across sovereign and air-gapped clouds
• Solving complex architectural trade-offs around concurrency, storage, and networking to ensure the platform remains resilient in high-consequence public sector environments
• Driving 'zero-waste' compute initiatives, optimising our engine and services to perform in resource-constrained or specialised regions (e.g., GovCloud)
• Partnering with Production Engineering to ensure all backend services meet the highest security standards and compliance guardrails while maintaining high availability

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Descript is revolutionising how traditional editing methodologies and AI technologies come together in every part of the creation process (recording, transcribing, editing, and sharing) to make it faster and easier than ever to create high-quality content.

What You'll Work On

Growth at Descript spans the full user journey,from initial signup to the point where customers can’t imagine working without us. This isn’t a role only focused on small tweaks; it’s about building systems that redefine how we grow.

Build the systems that makes growth possible

• Design and own the experimentation playbook , the frameworks, tooling, and best practices that let the whole team run faster, cleaner tests

• Architect personalisation and user journey systems that adapt the product experience based on who someone is and what they're trying to do

• Build the data pipelines and instrumentation that give us a real-time window into what's working

Run the experiments that move the needle

• Own A/B tests end-to-end: form the hypothesis, instrument the feature, ship it, analyse the results, make the call , repeat

• Own activation and onboarding flows , the early moments that turn a new signup into someone who gets it and stays

• Help establish the metrics culture , work with Data and Product to define what we're optimising for, and build toward it

Shape the product, not just the code

• Build full-stack across frontend and backend: snappy React UI, the APIs behind it, and everything in between

• Partner with Product and Design to define what we're building, not just how we build it

• Bring a systems thinker's perspective to the team to enhance the playbook , your judgement will carry real weight

What You Bring

Required

• 5+ years of professional software engineering experience (senior) or 8+ years (staff/lead)

• Strong command of TypeScript/JavaScript and React , you're the person others come to with hard frontend questions

• Deep familiarity with web fundamentals: HTML, CSS, REST APIs, performance optimisation

• Experience running A/B tests and product experiments , you understand what a good test looks like and what the results actually mean

• A genuine hunger to connect engineering work to business outcomes , you care about the metric, not just the merge

• Comfort with ambiguity: you can define the problem, not just solve one that's handed to you

• Strong written and verbal communication , you can explain a trade-off to an engineer and a result to a stakeholder

Why This Role, Why Now

The team exists, the product is genuinely loved, and the opportunity is wide open. This isn't a 'maintain what's working' role , it's a 'figure out what works, then scale it' role. If you want to own the full arc from idea to impact, and work on a product that creators actually use, this is it.

Benefits

• Generous healthcare package

• 401k matching programme

• Catered lunches

• Flexible vacation time

Fun fact about me: I love pineapple on pizza.

I am excited to apply for the Senior Software Engineer, Growth position at Descript. With my passion for building scalable systems and my experience in running A/B tests and product experiments, I believe I would be a great fit for this role. I am looking forward to discussing my application and how I can contribute to the growth of Descript.

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Our ideal candidate has a passion for database systems, storage systems, distributed systems, language design, or performance optimisation. They should be comfortable working towards a multi-year vision with incremental deliverables and be customer-oriented with a focus on having an impact. A minimum of 5 years of experience working in a related system is required, with a PhD in databases or distributed systems being optional.

In return, we offer a comprehensive benefits package and a commitment to diversity and inclusion. If you're excited about the opportunity to join our team and contribute to the development of next-generation database systems, please apply.

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The main responsibilities include:

• Lead an engineering team building the next-generation ETL features for the Databricks Lakeflow platform.
• Oversee sustained recruitment of top-tier talent, and upskilling talent on the team.
• Build processes to implement product vision and strategy, according to organisational goals and priorities.
• Build software that is not just high quality but easy to operate.
• Manage technical debt, including long-term technical architecture decisions and balance product roadmap.

What we look for:

• Minimum 3 years of experience in managing top-tier engineering teams.
• 5+ years experience building data infrastructure systems such as Apache Spark or database internals.
• A passion for database systems, storage systems, distributed systems, or performance optimisation.
• Experience working with product management, and directly with customers; ability to understand customer needs.
• Can ensure the team builds high quality and reliable infrastructure services.
• Experience being responsible for testing, quality, and Service Level Agreements of a product.
• Experience building and managing teams in a complex technical domain, such as on distributed data systems or database internals.
• Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards.
• Experience up-leveling teams via hiring top-notch talent and growing existing team members.

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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

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To be successful in this role, you'll need a PhD in databases or systems, a passion for database systems, storage systems, distributed systems, language design, and/or performance optimisation, and be motivated by delivering customer value and impact.

The pay range for this role is $140,000-$180,000 USD, and the total compensation package may also include eligibility for annual performance bonus, equity, and benefits.

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To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse (CIDR 2021 paper), open platforms that unify data warehousing and advanced analytics.

A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialised data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science.

As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art:

• Query compilation and optimisation
• Distributed query execution and scheduling
• Vectorised execution engine
• Data security
• Resource management
• Transaction coordination
• Efficient storage structures (encodings, indexes)
• Automatic physical data optimisation

We look for:

• A passion for database systems, storage systems, distributed systems, language design, or performance optimisation
• Experience working towards a multi-year vision with incremental deliverables
• Motivated by delivering customer value and impact
• 8+ years of experience working in a related system (preferred)

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 $192,000-$260,000 USD

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Key responsibilities include:

• Architect and develop pipelines to ingest and analyse data from network devices and other sources.
• Enhance scalability and performance by optimising computational processes and implementing solutions that scale with growing data and user demands.
• Innovate on product features by developing new features leveraging our network model to provide actionable insights.
• Collaborate with product teams to translate user needs into technical solutions.
• Technical leadership involves mentoring and guiding junior engineers, fostering a culture of excellence.
• Cross-functional collaboration is essential to ensure cohesive integration of services.

Requirements include:

• A Bachelor's degree in Computer Science or a related field, with a Master's or Ph.D. preferred.
• 8+ years of full lifecycle software development experience.
• Proven experience in backend development using Java, C++, or similar languages.
• Strong background in object-oriented design and development.

Technical skills include proficiency with databases, algorithms, and design for performance and scalability, as well as in-depth knowledge of software architecture, design patterns, and best practices.

Soft skills include excellent problem-solving abilities, strong communication skills, and the ability to work collaboratively in a fast-paced environment.

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Your strong foundation in data structures, parallel algorithms, and high-performance computing allows you to approach technical problems with both creativity and precision.

You thrive in collaborative R&D environments, valuing clean, scalable software architecture and rigorous technical standards.

As an emerging leader, you consistently inspire those around you, fostering a culture of innovation and excellence.

You are motivated by the opportunity to make a tangible impact, both on Synopsys' products and on the global engineering community.

Designing and implementing high-performance software components that drive the accuracy, scalability, and reliability of mesh generation software platforms.

Developing and optimising parallel and distributed algorithms to support advanced engineering workflows across large-scale structural, fluids, and electromagnetic simulations.

Collaborating closely with QA, product management, and hardware engineering teams to deliver robust, high-quality simulation capabilities.

Participating in code reviews, mentoring team members, and upholding rigorous standards for software architecture, maintainability, and performance.

Investigating and resolving complex technical issues reported by QA or customers to ensure stability, reliability, and customer success in production environments.

Contributing to the continuous improvement of development processes, tools, and best practices.

Advance the development of cutting-edge mesh generation software enabling next-generation engineering solutions across diverse physics domains.

Enhance product performance, scalability, and robustness by implementing efficient parallel and distributed algorithms.

Establish and promote best practices in software design, development, testing, and maintainability across the R&D team.

Support Synopsys' industry leadership in high-performance simulation technology and engineering software innovation.

Deliver high-quality, high-reliability solutions that drive meaningful impact across the global technology ecosystem.

Mentor and uplift team members, contributing to a culture of technical excellence and inclusive collaboration.

BS degree with 5+ years of relevant experience, MS degree with 3+ years of experience, or a PhD in Computer Science, Engineering, or a related field (or equivalent practical experience).

Strong proficiency in C++ and Python, with proven experience in data structures and parallel algorithms.

Deep understanding of software design principles.

Hands-on experience with version control systems (such as Git), working within Windows and Linux environments, debugging, and performance optimisation.

Professional experience in mesh generation, computational geometry, CAD, or related fields.

Exposure to CAD/CAE tools, semiconductor technology, or electronics design will be a plus.

Exhibits strong communication and leadership capabilities, indicating readiness to take on team leadership responsibilities soon.

A collaborative leader and mentor who inspires others to achieve their best.

An excellent communicator able to articulate complex technical concepts to diverse audiences.

Innovative, results-driven, and adaptable to fast-changing environments.

Proactive problem solver with a passion for continuous improvement.

Committed to fostering an inclusive and supportive team culture.

Join our globally distributed Synopsys meshing development team, where you will collaborate with talented engineers advancing the state-of-the-art in mesh generation, high-performance computing, and distributed simulation workflows.

Together, we are shaping the future of engineering through scalable, high-fidelity multi-physics simulation technologies.

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs.

Our total rewards include both monetary and non-monetary offerings.

Your recruiter will provide more details about the salary range and benefits during the hiring process.

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Join AVL and make a direct impact on shaping the future of Data, AI, and Mobility.

Your Responsibilities:

• Review and stabilise existing platform implementations (Databricks, Foundry – pipelines, Ontology schemas, Workshop applications, Functions, notebooks).
• Identify performance bottlenecks, technical debt, and governance gaps across data pipelines and application layers.
• Lead Ontology governance and design reviews, acting as a gatekeeper for all schema changes (Object Types, Links, Properties, Actions).
• Define and document target data architectures (ingestion, transformation, and consumption layers).
• Establish coding standards, naming conventions, repository structures, and Function versioning policies.
• Enforce code reviews and technical validation before production deployment through Foundry Branching and Proposal workflows.
• Define and implement a structured testing strategy (unit tests for Functions, integration tests, data quality checks, pipeline expectations).
• Design and improve CI/CD pipelines and Dev/Test/Prod promotion processes using Foundry Marketplace/DevOps.
• Automate deployments, rollbacks, and environment configurations.
• Create and maintain architecture documentation (ADRs, data lineage diagrams, Ontology schemas, data flow diagrams).
• Design reusable Workshop component libraries, custom widgets, and Slate application patterns.
• Design and validate new platform solutions aligned with strategy, security, and governance requirements.
• Mentor the development team on architectural thinking and platform best practices (40% hands-on coding, 60% architecture/leadership).

Your Profile:

• Master’s degree in Computer Science, Data Engineering, or a related field.
• 5+ years of experience in data engineering or platform architecture roles.
• Strong expertise in modern data platforms (Databricks, Snowflake, AWS Glue, Azure Synapse, or similar). Foundry experience is strongly preferred but not required.
• Advanced skills in Python (PySpark), SQL (Spark SQL), and TypeScript for backend logic and application development.
• Experience with distributed data processing (Spark architecture, partitioning strategies, performance optimisation).
• Strong understanding of relational databases (PostgreSQL, Oracle, or similar).
• Experience with CI/CD workflows, Git branching strategies, and automated testing in data environments.
• Solid experience in end-to-end ETL and data transformation processes.
• Proven experience in performance optimisation and scalable architecture design.
• Experience in defining development standards, interface contracts, and engineering best practices.
• Hands-on coding mindset: must write production code daily, not only review or document.
• Structured, analytical, and documentation-oriented approach.
• Strong communication and technical leadership skills, with very good proficiency in English and French.

Benefits:

• A role with true technical ownership: architecture, scaling, and governance decisions that directly impact production AI solutions.
• Complex projects that go beyond “just pipelines” – covering big data processing and large-scale ML/DL deployment.
• Opportunities to deepen your expertise in Databricks, cloud-native ML, and MLOps.
• A team where your input and technical decisions truly matter.
• A competitive package and benefits.

How to Apply:

If you have these qualifications and are looking for a new challenge, we encourage you to apply to discuss it further!

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

Responsibilities:

We are seeking a Linux OS and System Programming Subject Matter Expert to join our Infrastructure team. In this role, you'll work on accelerating and optimising our virtualisation and VM workloads that power our AI infrastructure. Your expertise in low-level system programming, kernel optimisation, and virtualisation technologies will be crucial in ensuring Anthropic can scale our compute infrastructure efficiently and reliably for training and serving frontier AI models.

• Optimise our virtualisation stack, improving performance, reliability, and efficiency of our VM environments
• Design and implement kernel modules, drivers, and system-level components to enhance our compute infrastructure
• Investigate and resolve performance bottlenecks in virtualised environments
• Collaborate with cloud engineering teams to optimise interactions between our workloads and underlying hardware
• Develop tooling for monitoring and improving virtualisation performance
• Work with our ML engineers to understand their computational needs and optimise our systems accordingly
• Contribute to the design and implementation of our next-generation compute infrastructure
• Share knowledge with team members on low-level systems programming and Linux kernel internals
• Partner with cloud providers to influence hardware and platform features for AI workloads

You may be a good fit if you:

• Have experience with Linux kernel development, system programming, or related low-level software engineering
• Understand virtualisation technologies (KVM, Xen, QEMU, etc.) and their performance characteristics
• Have experience optimising system performance for compute-intensive workloads
• Are familiar with modern CPU architectures and memory systems
• Have strong C/C++ programming skills and ideally experience with systems languages like Rust
• Understand Linux resource management, scheduling, and memory management
• Have experience profiling and debugging system-level performance issues
• Are comfortable diving into unfamiliar codebases and technical domains
• Are results-oriented, with a bias towards practical solutions and measurable impact
• Care about the societal impacts of AI and are passionate about building safe, reliable systems

Strong candidates may also have experience with:

• GPU virtualisation and acceleration technologies
• Cloud infrastructure at scale (AWS, GCP)
• Container technologies and their underlying implementation (Docker, containerd, runc, OCI)
• eBPF programming and kernel tracing tools
• OS-level security hardening and isolation techniques
• Developing custom scheduling algorithms for specialised workloads
• Performance optimisation for ML/AI specific workloads
• Network stack optimisation and high-performance networking
• Experience with TPUs, custom ASICs, or other ML accelerators

Representative projects:

• Optimising kernel parameters and VM configurations to reduce inference latency for large language models
• Implementing custom memory management schemes for large-scale distributed training
• Developing specialised I/O schedulers to prioritise ML workloads
• Creating lightweight virtualisation solutions tailored for AI inference
• Building monitoring and instrumentation tools to identify system-level bottlenecks
• Enhancing communication between VMs for distributed training workloads

Deadline to apply:

None. Applications will be reviewed on a rolling basis.

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 the authenticity of an email or a request, please reach out to us directly.

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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.

At Anthropic, we are building some of the most complex and large-scale AI infrastructure in the world. As that infrastructure scales rapidly, so does the imperative to optimise how we use it. As a Software Engineer for Compute Efficiency on the Capacity team, you will play a central role in making our systems more performant, cost-effective, and sustainable—without compromising reliability or latency.

You will work across the full infrastructure stack, from cloud platforms and networking to application-level performance, and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world. You will help with building the telemetry, cost attribution, and optimisation frameworks that ensure every dollar of our infrastructure investment delivers maximum value. This is a high-impact, cross-functional role at the intersection of systems engineering, financial optimisation, and AI infrastructure.

Responsibilities

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilisation, and costs across our cloud and datacentre fleets.

• Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimise their resource consumption.

• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

• Partner closely with cloud service providers and internal stakeholders to optimise cluster configurations, workload placement, and resource utilisation across AI training and inference workloads—including large-scale clusters spanning thousands to hundreds of thousands of machines.

• Develop and champion engineering practices around efficiency, driving a culture of performance awareness and cost-conscious design across Anthropic.

• Collaborate with research and product teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.

• Drive architectural improvements and code-level optimisations across multiple services and platforms to deliver measurable utilisation and performance gains.

You may be a good fit if you:

• Have 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams as a software engineer or tech lead

• Deep expertise in distributed systems at scale, with a strong focus on infrastructure reliability, scalability, and continuous improvement.

• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)

• Hands-on experience with cloud infrastructure, including Kubernetes, Infrastructure as Code, and major cloud providers such as AWS or GCP.

• Experience optimising end-to-end performance of distributed systems, including workload right-sizing and resource utilisation tuning.

• You possess a deep curiosity for how things work under the hood and have a proven ability to work independently to solve opaque performance issues

• Experience designing or working with performance and utilisation monitoring tools in large-scale, distributed environments.

• Strong problem-solving skills with the ability to work independently and navigate ambiguity.

• Excellent communication and collaboration skills—you will work closely with internal and external stakeholders to build consensus and drive projects forward.

Strong candidates may have:

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.

• Low level systems experience, for example linux kernel tuning and eBPF

• Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

• Published work in performance optimisation and scaling distributed systems

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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic

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

About the role:

Claude.ai is Anthropic's flagship consumer product, spanning web, mobile, desktop, and browser extensions—and it's growing fast. The UI Platform team owns the foundational layer that makes all of this possible: the shared infrastructure, components, APIs, and tooling that let every other product team at Anthropic ship quickly, reliably, and with confidence.

As a Software Engineer on this team, you'll be hands-on building the platform that other engineers depend on every day. This means designing and shipping shared components and design-system-level abstractions, evolving the backend-for-frontend (BFF) APIs that power our client applications, and improving the build, deploy, and observability systems that keep Claude.ai running smoothly across surfaces. Your work will directly shape how fast teams across Anthropic can innovate—and how stable their experiences are when they do.

This is a great fit if you care deeply about developer experience and want your engineering work to have outsized leverage: instead of shipping one feature, you're building the tools and systems that make dozens of features possible.

Responsibilities:

• Design and build shared UI components, libraries, and abstractions that product teams across Anthropic use to ship consistently and efficiently on web and mobile
• Contribute to the BFF API layer that powers Claude.ai's client applications—thinking carefully about clean contracts, performance, and reliability at the boundary between frontend and backend
• Improve developer velocity across the organisation by reducing friction in our build, deploy, and testing pipelines
• Work on performance and reliability: identify and resolve latency issues, improve observability, and help establish high standards that the rest of the platform team can build on
• Partner closely with product engineering teams to understand their needs, unblock them when possible, and shape platform investments around where the most impact is
• Help maintain and evolve documentation and tooling that make the platform approachable for engineers joining or building on top of it

You may be a good fit if you:

• Have 5+ years of software engineering experience, with significant time spent building shared platforms, developer tools, or infrastructure that other engineers rely on
• Have strong practical skills in modern web technologies (React, TypeScript, Next.js) and experience designing or consuming APIs that serve frontend applications
• Care about developer experience and have a track record of building things that make other engineers more productive
• Have solid instincts around reliability, observability, and performance—and enjoy operationalising those instincts in production systems
• Thrive in fast-paced, collaborative environments and enjoy working closely with cross-functional partners
• Pick up slack, even if it goes outside your job description

Strong candidates may also have experience with:

• Building shared component libraries or design systems for multiple surfaces (web, mobile, desktop)
• BFF architectures and API patterns that balance flexibility with consistency across client platforms
• Performance optimisation and latency reduction in consumer-facing applications
• CI/CD, build systems, and deployment automation
• Observability and monitoring (metrics, logging, tracing)
• Working on AI/ML products or in rapidly evolving product environments

Candidates need not have:

• 100% of the skills needed to perform the job
• Formal certifications or education credentials

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.

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

About the Role:

Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.

This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimisation, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.

Responsibilities:

• Own critical aspects of our production pretraining pipeline, including model operations, performance optimisation, observability, and reliability
• Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
• Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
• Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
• Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
• Add new capabilities to the training codebase, such as long context support or novel architectures
• Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
• Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned

You May Be a Good Fit If You:

• Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
• Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
• Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
• Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
• Excel at debugging complex, ambiguous problems across multiple layers of the stack
• Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
• Are passionate about the work itself and want to refine your craft as a research engineer
• Care about the societal impacts of AI and responsible scaling

Strong Candidates May Also Have:

• Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
• Contributed to open-source LLM frameworks (e.g., open\_lm, llm-foundry, mesh-transformer-jax)
• Published research on model training, scaling laws, or ML systems
• Experience with production ML systems, observability tools, or evaluation infrastructure
• Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence

What Makes This Role Unique:

This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends.

However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding.

We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you.

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.

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

About the Team

Our team is organised around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows.

About the role

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimisation, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.

Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity.

Responsibilities:

• Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
• Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
• Scaling research ideas from prototype to production
• Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
• Implement distributed training systems and performance optimisations to support large-scale model development

You may be a good fit if you:

• Have 8+ years of ML research experience
• Are familiar with large scale language model training, evaluation, and inference pipelines
• Enjoy obsessively iterating on immediate blockers towards longterm goals
• Thrive working collaboratively to solve problems
• Have expertise in performance optimisation and distributed computing systems
• Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems
• Can translate research concepts into scalable engineering solutions
• Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems

Strong candidates may also have:

• Expertise with performance optimisation for language model inference and training
• Experience with computer use automation and agentic AI systems
• A history working on reinforcement learning approaches for complex task completion
• Knowledge of containerisation technologies (Docker, Kubernetes) and cloud deployment at scale
• Demonstrated ability to work across multiple domains (language modelling, systems engineering, scientific computing)
• Have experience with VM/sandboxing/container deployment and large-scale data processing
• Experience working with large scale data problem solving and infrastructure
• Published research or practical experience in scientific AI applications or long-horizon reasoning

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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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.

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