Key responsibilities include:

• Drive strategy that fields safe and secure performant agents on embedded warfighting compute.
• Manage a cohort of cleared machine learning engineers, researchers, and product managers.
• Provide deep technical leadership to team on design, development, and deployment of advanced AI solutions.
• Leverage and shape the world's largest defense robotics data set to develop cutting-edge AI capabilities.
• Coordinate with internal testing and evaluation team(s) to design specialized evaluation benchmarks for defense use-cases.
• Partner with US-based Frontier AI Labs to revolutionize the employment of autonomy in embedded hardware.

Required qualifications include:

• Management experience leading and growing AI/ML teams.
• Experience deploying AI-technologies into classified environments (e.g., disconnected, air-gapped, etc.).
• Expertise in deep learning techniques and the latest generative AI technologies (Agents, Vision-Language Action models, etc.).
• Strong programming skills.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.

Preferred qualifications include:

• Experience with edge-deployed ML systems.
• Prior work in Defense Tech and/or Start Ups.
• Active U.S. Top Secret SCI security clearance.

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Responsibilities:

• Lead and execute complex data science projects that directly advance our drug development portfolio
• Develop and implement sophisticated models for therapeutic hypothesis evaluation, including patient stratification and biomarker identification
• Design and create AI models for modernizing clinical trial evaluations, including surrogate endpoints
• Aid in the development and training of AI agents to automate and optimize biomedical workflows
• Collaborate cross-functionally with clinical, technical, and research teams
• Present complex analytical findings to senior stakeholders, including executive leadership

About You:

• Required Qualifications:

+ PhD in computational sciences or life sciences + 3+ years of post-academic experience in life sciences (biotech, pharma, consulting) + Strong programming skills, particularly in Python + Extensive experience in multi-modal bioinformatics analysis

• Preferred Qualifications:

+ Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases + Strong background in machine learning and deep learning, particularly in biological applications + Experience with large language models (LLM) + Demonstrated ability to collaborate effectively with engineering teams on production systems + Strong communication skills with proven ability to present complex technical findings to senior stakeholders

Total Compensation Range: $170,000 - $215,000

Where We Hire:

Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with a hybrid model requiring 3 days per week in office. Applicants from the Research Triangle (NC) and San Francisco Bay Area may also be considered.

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We are looking for a skilled Senior Site Reliability Engineer to join our Tenant Services, Geo team. As a Senior Site Reliability Engineer, you will be responsible for ensuring the smooth operation of our user-facing services and production systems.

About Us

GitLab is the intelligent orchestration platform for DevSecOps. It enables organisations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation.

Responsibilities

• Execute Dedicated Geo migrations and cutovers end-to-end, including planning, pre-cutover validation, execution, and post-cutover verification and cleanup.
• Join the team's shift and weekend coverage rotation for Dedicated cutovers across EMEA and US hours, and participate in the SaaS Site Reliability Engineering (SRE) on-call rotation to respond to incidents that impact GitLab.com availability.
• Operate and improve the Geo operational surface for Dedicated, including:
• Environment preparation and data hygiene checks prior to migrations.
• Execution of replication, validation, and cutover procedures.
• Handling Geo-related escalations from Support and internal partners.
• Design, build, and maintain automation, tooling, and runbooks that make migrations, cutovers, and Geo escalations as 'boring' and repeatable as possible.
• Run our infrastructure with tools such as Ansible, Chef, Terraform, GitLab CI/CD, and Kubernetes; contribute improvements back to GitLab's product and infrastructure where appropriate.
• Build and maintain monitoring, alerting, and dashboards that:
• Detect symptoms early, not just outages.
• Track migration and cutover success rates, duration, rollback frequency, and related SLOs.
• Collaborate closely with:
• The core Geo team on improving Geo features and operability.
• Dedicated migrations and Support on migration planning, customer communications, and escalation handling.
• Other Infrastructure teams on capacity planning, disaster recovery, and reliability improvements.
• Contribute to readiness reviews, incident reviews, and root cause analyses, turning learnings into changes in automation, process, or product.
• Document every action, including runbooks, architecture decisions, and post-incident reviews, so your findings turn into repeatable practices and automation.
• Proactively identify and reduce toil by automating repetitive operational work and simplifying migration workflows.

Requirements

• Experience operating highly-available distributed systems at scale, ideally in a SaaS environment with customer-facing SLAs.
• Hands-on experience with at least one major cloud provider (e.g., Google Cloud Platform or Amazon Web Services), including networking, storage, and managed services.
• Experience with Kubernetes and its ecosystem (e.g., Helm), including deploying and troubleshooting workloads.
• Experience with infrastructure as code and configuration management tools such as Terraform, Ansible, or Chef.
• Strong programming skills in at least one general-purpose language (preferably Go or Ruby) and proficiency with scripting (e.g., Shell, Python).
• Experience with observability systems (e.g., Prometheus, Grafana, logging stacks) and using metrics and logs to troubleshoot performance and reliability issues.
• Practical exposure to data replication, backup/restore, or migration scenarios (e.g., database replication, storage replication, or Geo-like technologies) where data integrity and downtime risk must be carefully managed.
• Comfort participating in an on-call rotation, investigating incidents across the stack, and driving follow-through on corrective actions.
• Ability to engage directly with enterprise customers during migrations and incidents, including on live calls and through clear written updates.
• Ability to clearly define problems, propose options, and think beyond immediate fixes to improve systems and processes over time.
• Ability to be a 'manager of one': self-directed, organized, and able to drive work to completion in a remote, asynchronous environment.
• Strong written and verbal communication skills, with a bias toward clear, asynchronous documentation and collaboration.
• Alignment with our company values and a commitment to working in accordance with those values.

Nice to Have

• Experience working with disaster recovery technologies.
• Experience with managed/hosted environments similar to GitLab Dedicated, including regulated or compliance-sensitive customers (e.g., SOC2, ISO).
• Prior work on large-scale data migrations or cutovers where customer data integrity, performance, and downtime risk had to be carefully balanced.
• Hands-on experience designing and operating database replication, backup/restore, and cutover workflows (for example, PostgreSQL or cloud-managed equivalents such as AWS RDS), including planning and executing low-risk migrations for large datasets.
• Experience with multi-tenant architectures, sharding, or routing strategies in high-traffic SaaS platforms.
• Familiarity with GitLab (self-managed or SaaS), and/or contributions to open source projects.

Benefits

• Benefits to support your health, finances, and well-being
• Flexible Paid Time Off
• Team Member Resource Groups
• Equity Compensation & Employee Stock Purchase Plan
• Growth and Development Fund
• Parental leave
• Home office support

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The ideal candidate will have a strong background in computer science, robotics, machine learning, or a related field, and experience integrating agents into classical systems. They will also have a proven track record of novel application and experience including first-author publications, participation in peer-reviewed conferences, contribution to open-source projects, and demonstrated contribution to the ML and AI community.

In addition to your technical expertise, you will be a strong communicator and collaborator, able to work effectively with cross-functional teams to drive results. You will also be comfortable working in a fast-paced environment and adapting to changing priorities.

If you are a motivated and experienced engineer looking to join a dynamic team and contribute to cutting-edge technology, we encourage you to apply.

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As our models become more capable, the infrastructure supporting secure execution environments becomes increasingly critical. You'll work on distributed systems that must operate reliably at significant scale while maintaining strong security boundaries. Your work will directly support Anthropic's mission to develop AI systems that are safe, beneficial, and trustworthy.

Responsibilities:

• Design, build, and operate distributed backend systems that power secure sandboxed execution environments
• Scale infrastructure to meet growing research and product demands while maintaining reliability and performance
• Implement and maintain serverless architectures and container orchestration systems
• Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions
• Develop monitoring, alerting, and observability systems to ensure operational excellence
• Participate in on-call rotations and incident response to maintain system reliability
• Contribute to infrastructure automation and tooling that improves developer productivity
• Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees

You may be a good fit if you:

• Have 5+ years of experience building and operating backend infrastructure at scale
• Have deep expertise in distributed systems design and implementation
• Have strong operational experience, including debugging complex production issues
• Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)
• Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications
• Are comfortable working with infrastructure as code and modern DevOps practices
• Have strong programming skills in languages such as Python, Go, or Rust
• Are results-oriented with a bias towards flexibility and impact
• Care about the societal impacts of your work and are motivated by Anthropic's mission

Strong candidates may also have experience with:

• Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)
• Designing and implementing secure multi-tenant systems
• High-performance computing environments or ML infrastructure
• Linux systems internals, including namespaces, cgroups, and seccomp
• Network security and isolation techniques
• Building systems that support research workflows and rapid iteration

The annual compensation range for this role is $300,000-$405,000 USD.

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.

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Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Responsibilities:

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
• Provide white-glove deployment support for Anthropic products in enterprise environments.
• Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
• Build long-term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Travel frequently (25-50%) to customer sites to build in-person with customers.
• Be a champion for Anthropic's mission in the field.

You May Be a Good Fit If You Have:

• 4+ years of experience in a technical, customer-facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc) and experience shipping production applications.
• High agency with an ability to navigate ambiguity present in complex organizations.
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
• Passion for advancing safe, beneficial AI systems through creative technical applications.
• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.
• A background in financial services, healthcare/life sciences, or another enterprise vertical is a plus.
• Experience with enterprise IT systems and/or AI deployment patterns is a plus.

Annual Salary: £225,000-£255,000 GBP

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Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Responsibilities:

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
• Provide white-glove deployment support for Anthropic products in enterprise environments.
• Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
• Build long-term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Travel frequently (25-50%) to customer sites to build in-person with customers.
• Be a champion for Anthropic's mission in the field.

You May Be a Good Fit If You Have:

• 4+ years of experience in a technical, customer-facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.
• Native or C1 German speaker with fluent English proficiency
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc) and experience shipping production applications
• High agency with an ability to navigate ambiguity present in complex organizations.
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
• Passion for advancing safe, beneficial AI systems through creative technical applications.
• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.
• A background in financial services, healthcare/life sciences, or another enterprise vertical is a plus.
• Experience with enterprise IT systems and/or AI deployment patterns is a plus.

Annual Compensation Range: €205,000-€220,000 EUR

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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.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Responsibilities:

• Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success

• Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation

• Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API

• Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API

• Lead hands-on technical workshops and code reviews with customer engineering teams

• Identify common design patterns and contribute insights back to our Product and Engineering teams

• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks

• Travel occasionally to customer sites for workshops, implementation support, and building relationships

• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have:

• 4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers

• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale

• Strong programming skills with proficiency in Python and experience building production applications

• Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.

• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems

• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity

• Passion for advancing safe, beneficial AI systems through creative technical applications

• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

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. 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, 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

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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.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Responsibilities:

• Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success
• Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation
• Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API
• Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API
• Lead hands-on technical workshops and code reviews with customer engineering teams
• Identify common design patterns and contribute insights back to our Product and Engineering teams
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
• Travel occasionally to customer sites for workshops, implementation support, and building relationships
• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have:

• 4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale
• Strong programming skills with proficiency in Python and experience building production applications
• Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.
• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
• Passion for advancing safe, beneficial AI systems through creative technical applications
• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach
• Fluent in both Korean and English

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, 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

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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

As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems. Our FDEs engage with customers to accelerate the adoption of existing products and create new applications built on our models.

Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

You May Be a Good Fit If You Have

• 4+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.

• Native or C1 German speaker with fluent English proficiency

• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.

• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like TypeScript, Java, etc) and experience shipping production applications

• High agency with an ability to navigate ambiguity present in complex organisations.

• High cooperation mindset for cross-organisational collaboration, balancing competing priorities with integrity.

• Passion for advancing safe, beneficial AI systems through creative technical applications.

• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.

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.

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Location

San Francisco

Employment Type

Full time

Department

Research

Compensation

• $250K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Role

As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed.

We expect you to:

• Have strong programming skills

• Have experience working in large distributed systems

• Be excited about OpenAI’s approach to research

Nice to have:

• Interested in and thoughtful about the impacts of AI technology

• Past experience in creating high-performance implementations of deep learning algorithms

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Software Engineer, Compute - Storage

Location

San Francisco; New York City

Employment Type

Full time

Location Type

Hybrid

Department

Scaling

Compensation

• $230K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

Storage Infrastructure provides APIs for data access, placement, and lifecycle management, while ensuring that the storage systems’ capacity, throughput, and IOPs satisfy the needs of our AI researchers. Scalability, reliability, security, and usability are the core concerns of the team.

About the Role

As an engineer on the Storage Infrastructure team, you will design, build, and operate Exascale systems to scalably and reliably manage our research data across multiple regions.

We’re looking for distributed systems engineers who have worked on exascale data management systems or distributed filesystems.

In this role, you will:

• Develop software to manage exascale data, and make it accessible to researchers

• Drive the reliability, predictability, and cost effectiveness of our storage systems

• Interface with researchers to understand and accommodate data use-cases

• Ensure the security of our critical datasets

You might thrive in this role if you:

• Have a deep understanding of distributed systems principles and a proven track record in designing and building scalable, reliable, and secure storage solutions.

• Possess strong programming skills

• Have experience working in public clouds (especially Azure)

• Are familiar with AI/ML data access patterns

• Bias for action and comfort building in a fast paced, dynamic environment

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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What you'll do

We are looking for a skilled Full Stack Engineer to partner closely with Search, AI, Design, and Product teams to ship experiments and rapidly iterate on insights.

• Partner closely with Search, AI, Design, and Product teams to ship experiments and rapidly iterate on insights.
• Drive the launch of new features, experiments, and campaigns in a fast-paced, evolving environment.
• Architect and implement systems that integrate new tools with existing pipelines and LLM - or agent-based evaluation frameworks.
• Build, refine, and maintain the core components that power Perplexity's frontend experience.

What you need

• Strong programming skills and the ability to work effectively across the full stack.
• Solid coding fundamentals and experience contributing to both frontend and backend systems.
• Self-driven mindset with strong ownership and follow-through.
• Passion for building high-quality products, rapid prototyping, experimentation, and creating accessible user experiences.

Why this matters

As a Full Stack Engineer at Perplexity, you will have the opportunity to work on cutting-edge AI-powered product features and contribute to the development of our frontend experience. Your skills and expertise will be essential in helping us to build and ship high-quality products that meet the needs of our users.

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What you'll do

• Design, build, and scale financial systems and infrastructure including revenue recognition, billing automation, invoicing, and payment processing.
• Develop and maintain business intelligence platforms, data pipelines, and reporting dashboards that provide real-time visibility into financial metrics and business performance.

What you need

• Strong programming skills with the ability to work across the full stack (backend services, APIs, databases, and web interfaces).
• Experience building financial systems, billing platforms, or working with financial data at scale.

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What you'll do

• Design, build, and scale new 0→1 growth products and features across web and mobile.
• Work closely with Product, Design, and Data to define hypotheses, ship experiments, and iterate quickly based on results.

What you need

• Strong programming skills with the ability to work across the full stack (backend, APIs, and modern web frontends).
• Self-motivated and comfortable taking ownership of ambiguous, high-impact projects end to end.

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What you'll do

• Building new 0-1 products at high scale
• Working closely with Product, Design, and Data to ship experiments and learn
• Launching new features, experiments, campaigns, and partnerships in a fast-moving environment
• Building core growth infrastructure such as notification platforms, ad attribution, and more

What you need

• Strong programming skills with the ability to work across the full stack
• Self-motivated with a willingness to take ownership of tasks
• Good quantitative understanding of data and experimentation

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What you'll do

We are hiring Jun 2026 - Jan 2027 Software & Data Interns across the following roles:

1. AI Data Engineer Intern
2. AI Software Engineering Intern
3. Data Engineer Intern (Big Data)
4. Data Scientist Intern (Big Data)
5. Data Analyst Intern (Big Data)
6. Software Engineer Intern (Razer Gold)
7. AI Engineer Intern (Razer Gold)
8. Data Engineering Intern (IT Services)
9. Site Reliability Engineer Intern (Cloud Services)
10. Software Engineer Intern (Cloud Services)

What you need

• Strong programming skills in languages such as Python, Java, or C++
• Experience with data structures and algorithms
• Familiarity with machine learning and data analysis tools

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What you'll do

• You will work with cross-functional teams including Content Management & Delivery, Messaging, Segmentation, Recommendation, and Experimentation to streamline the live services workflow.
• You will evaluate where and how EA's live service solutions, studio tech stacks, and vendor solutions can work together and help to achieve both engineering and business goals in an efficient and cost-effective manner.

What you need

• Bachelor/Master’s degree in Computer Science/related field or relevant experience.

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What you'll do

• You will work with cross-functional teams including Content Management & Delivery, Messaging, Segmentation, Recommendation, and Experimentation to streamline the live services workflow.
• You will evaluate where and how EA's live service solutions, studio tech stacks, and vendor solutions can work together and help to achieve both engineering and business goals in an efficient and cost-effective manner.

What you need

• Bachelor/Master’s degree in Computer Science/related field or relevant experience.

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What you'll do

• Research and develop new technologies and techniques to improve the Unreal Engine and other Epic Games products
• Collaborate with other engineers and researchers to develop and implement new technologies and techniques

What you need

• PhD in Computer Science, Machine Learning, Mathematics, or related field
• Strong programming skills in languages such as Python and C++
• Experience with machine learning and computer vision

XML job scraping automation by YubHub