As a highly experienced applications engineer with deep expertise in emulation platforms and methodologies, you will lead customer engagements for emulation solutions, providing technical guidance and support to optimize verification workflows.

Designing and implementing advanced emulation strategies for complex SoC and ASIC projects, collaborating with R&D teams to influence product development and ensure customer requirements are addressed.

Developing and delivering technical presentations, training, and workshops for internal teams and customers, troubleshooting and resolving challenging emulation issues, ensuring customer satisfaction and project success.

Mentoring junior engineers, fostering knowledge sharing and professional growth within the team.

Accelerate verification cycles for industry-leading semiconductor companies through innovative emulation solutions, enhance the adoption and effectiveness of Synopsys emulation platforms across a diverse customer base.

Drive technical excellence by implementing best practices and leading critical customer projects to success, shape product direction by providing valuable feedback and insights to R&D teams.

Foster collaborative relationships with customers, building trust and long-term partnerships, contribute to Synopsys' reputation as the premier provider of advanced verification and emulation technologies.

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Our vision is to transform product design, development, and characterization to enable delivery of new medicines to patients. In this role, you will lead analytical strategy and delivery for oral solid dosage (OSD) forms and, as needed, inhaled and/or parenteral products from early development through clinical supply and toward commercialization.

As the analytical project/skill lead, you will partner across formulation, engineering, biopharmaceutics, manufacturing, QA and Regulatory to deliver robust methods, efficient control strategies, and submission-ready documentation. You will also help establish and optimize OSD laboratory capabilities at the Durham site, champion laboratory automation, and encourage adoption of modern data analytics and AI/ML tools to accelerate development and interpretation.

We work, on average, a minimum of three days per week from the office. We balance the expectation of being in the office while respecting individual flexibility.

Responsibilities include, but are not limited to:

• Project leadership: Act as analytical skill lead to secure major drug product deliveries, applying a risk-based, flexible approach to prioritization, resources, and timelines across modalities and dosage forms; integrate analytical plans with global teams and external partners/CMOs.

• Analytical strategy & control: Define and own a phase-appropriate analytical control strategy aligned with CMC expectations across clinical phases; harmonize methods and embed lifecycle management to ensure robust, efficient control.

• Method development & validation: Design, develop, validate, transfer, and lifecycle manage analytical methods for OSD (e.g., HPLC/UPLC, LC–MS, dissolution, impurity profiling, stability-indicating capability); establish scientifically supported system suitability, specifications, and fit-for-purpose sample preparation; ensure readiness for GMP execution with clear documentation and analyst guidance. Support inhaled and/or parenteral methods as needed.

• Characterization & performance: Lead drug product characterization, comparability, and stability programs; direct forced degradation studies; for inhaled products where required, support aerodynamic performance assessments (e.g., impactor analysis).

• CMC & regulatory: Author and review analytical CMC content for IND/IMPD/NDA/MAA; prepare validation reports, method transfer documents, and specifications; lead responses to regulatory queries and support shelf life assignment with appropriate statistics.

• Cross-functional collaboration: Work closely with formulators, engineers, supply and manufacturing sites, QA, Regulatory, and external partners/CMOs to integrate analytical deliverables into project plans and clinical manufacturing.

• Durham lab capability & technology: Champion laboratory automation for sample preparation, method execution, and data analysis under GxP control.

• Problem-solving: Lead complex investigations, root cause analyses, and data integrity assessments; apply structured problem-solving (e.g., Six Sigma) and statistics to drive timely resolution and preventive actions.

• Digital, data & innovation: Apply DoE and statistics for method robustness and understanding; use ELN/CDS and statistical tools; promote AI/ML, chemometrics, and predictive analytics to enhance interpretation, specification setting, and development speed; enable learning and standardization across projects; chip in to patenting and/or publishing.

• Quality & governance: Ensure GxP compliance where applicable, data integrity, rigorous study design, and clear communication to governance bodies.

Minimum Qualifications:

• Bachelor’s (12+ years), Master’s (6+ years), or PhD (or equivalent experience) in Analytical Chemistry, Pharmaceutical Sciences, Biochemistry, Biotechnology, or related field.

• Significant experience in pharmaceutical analytical science with current knowledge of regulatory CMC requirements for clinical and/or marketing applications.

• Demonstrated experience in analytical development for oral solid dosage forms; additional experience with inhaled and/or parenteral products preferred.

• Consistent record leading teams and/or scientific projects within a global organization and with external partners/CMOs; ability to influence cross-functional strategies.

• Strong proficiency with chromatographic techniques (HPLC/UPLC; LC–MS), dissolution, and complementary methodologies; for inhaled products, familiarity with aerosol performance characterization is a plus.

• Hands-on experience in method development (including use of supporting software), validation, transfer, and lifecycle management under ICH guidelines and phase-appropriate frameworks.

• Experience authoring analytical CMC content for submissions and responding to regulatory queries across clinical development.

• Experience working in a GMP/GxP environment; familiarity with instrument/equipment qualification, calibration, and maintenance expectations.

• Excellent communication, customer management, and influencing skills; ability to operate confidently and collaboratively across global, cross-disciplinary environments.

• Demonstrated ability to troubleshoot technical challenges and drive data-driven decisions.

• Fundamental digital and data capability relevant to analytical development, including:

• Proficiency with multivariate experimental design and basic DoE concepts for method and process understanding

• Working knowledge of statistics for analytical science (e.g., regression, ANOVA, capability/variation analysis, stability trending, OOS/OOT investigation)

• Practical use of ELN/CDS and statistical software (e.g., JMP or Minitab) for data analysis and reporting

Preferred Qualifications:

• Strategic chromatographic and separation science leadership: define orthogonal method suites (e.g., RP, HILIC, ion exchange, SEC, SFC, CE) to secure impurity resolution and stability-indicating capability; apply LC–MS(/MS) for structure confirmation and quantitation; use multidimensional LC and targeted DoE to accelerate development and set robust specifications; harmonize methods across sites with clear comparability criteria; embed lifecycle management and coach teams through complex separations (e.g., peptides, oligonucleotides, challenging matrices).

• OSD focus: Support with establishing, equipping, and optimizing OSD test equipment and processes at the Durham site.

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Your responsibilities will include: Implementing client features and systems in C++. Extending existing client systems and creating new ones. Working with designers, producers, content creators and other engineers to design and develop game features. Writing technical design documents detailing software requirements. Writing cross-platform code with performance and memory usage in mind. Debugging code to document and fix bugs. Solving challenging technical problems in a dynamic environment to support active live service.

We are looking for someone with a strong working knowledge of modern C++, experience implementing complex game subsystems, and a strong understanding of geometry, linear algebra, calculus, and physics as they pertain to transformations and motions in 3D space.

If you have experience with graphics libraries (DirectX/OpenGL/Metal), desktop development, Windows platform and development tools (e.g. Visual Studio or other programming IDEs), skills debugging complex applications, and experience optimizing existing game code to be more performant, you will be a great fit for this role.

We offer a competitive salary range of $122,300 - $170,700 CAD per year, depending on location, as well as a package of benefits including vacation, sick time, paid top-up to EI/QPIP benefits, extended health/dental/vision coverage, life insurance, disability insurance, retirement plan, and bonus and equity opportunities.

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Job Title: Site Reliability Engineer II

Pogo has been the leader in online casual games since 1998. Featuring a growing library of 60+ titles spanning popular genres like Solitaire, Mahjong, Match 3, and more, Pogo exists to be the best destination for online casual games. We strive to produce high-quality HTML5-powered games with sophisticated metagames and social mechanics, all while working seamlessly across desktop, tablet and mobile. Our fans and subscribers come to Pogo for fresh content, daily challenges, great events, new games, and a live service that delivers! We are looking for a Site Reliability Engineer on Pogo engineering to help maintain and work towards continuous improvement of infrastructure for the Pogo platform and games.

In this key role, you will report directly to the Associate Technical Director and have a high level of interaction with Pogo engineering team members, development directors and EA central teams. Pogo Engineering manages the Pogo platform that consists of Progressive WebApp and Java Backend deployed on AWS that supports more than 60 HTML5 games. As part of the engineering team, you will help build, maintain and continuously improve Pogo’s infrastructure for games and platform.

Key Responsibilities:

• Build and maintain CI/CD pipelines for several projects and work towards continuous improvement.
• Keep Pogo infrastructure up-to-date by applying updates in timely manner
• Implement monitoring and alerting systems for service degradations
• Identify and deploy security measures by performing vulnerability assessments and risk management.
• Encourage and build automated processes whenever possible.

Qualifications:

• Bachelor's degree in Computer Science or related field, or equivalent training and professional experience
• 4+ years of experience as a DevOps/Site Reliability engineer
• Proficient in CI/CD technologies like Maven, Gradle, Jenkins, Gitlab CI/CD
• Proficient in cloud platform like AWS
• Expertise in containerization with Docker/Kubernetes and orchestration tools Ansible/Puppet
• Proficiency in cloud-based DevOps practices like Terraform
• Experience with shell scripting and knowledge of scripting languages like Ruby, Python
• Experience with monitoring tools like Prometheus, Grafana, Cloudwatch
• Experience with load testing, troubleshooting, and optimizing performance of web services
• Experience with Scrum/Agile development methodologies

Nice To Have:

• Experience in game industry is a plus

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EA SPORTS is one of the leading sports entertainment brands in the world, with top-selling videogame franchises, award-winning interactive technology, fan programs, and cross-platform digital experiences.

As one of the largest sports entertainment platforms in the world, EA SPORTS FC is redefining football with genre-leading interactive experiences, connecting a global community of fans to The World's Game through innovation and unrivaled authenticity.

With more opportunity than ever to design, innovate and create new, immersive experiences that bring joy, inclusivity, and connection to fans everywhere, we invite you to join our passionate and dynamic team as we pioneer the future of football fandom.

Senior Full Stack Engineers are key drivers behind the technology that powers our games and the experiences millions of players love. In this role, you’ll design and build scalable backend services, data pipelines, and APIs that move and process massive amounts of real-time game data. As part of the Gameplay Advance team at EA, you’ll work alongside world-class engineers to push gameplay technology forward,solving complex technical challenges, influencing architecture, and helping shape the future of how our games are built and played.

Your Responsibilities:

• Troubleshoot and resolve complex production issues quickly across the full technology stack (backend, frontend, and data).

• Design, develop, and maintain scalable backend systems and data pipelines using Python and modern frameworks.

• Setup and optimize data streaming solutions to ensure real-time data processing and reliability.

• Design, build, and maintain cloud-hosted data pipelines and services used in production

• Collaborate closely with cross-functional partners, including central platform teams and DevOps, to deliver reliable solutions

Your Qualifications:

Please note that you do not need to qualify for all requirements to be considered. We encourage you to apply if you can meet most of the requirements and are comfortable opening a dialog to be considered.

• Bachelor’s or Master’s degree in Computer Science, or 8+ years of hands-on professional software development experience

• Experience building, shipping, and supporting scalable, cloud-hosted services

• Proficiency in multiple programming languages and frameworks, including Python and C++

• Strong understanding of client/server architectures, HTTP, RESTful APIs, and WebSocket-based data streaming

• Experience contributing to modern web application frontends

• Hands-on experience with machine learning data frames, including tools like Polars

• Experience deploying and operating services using Docker and Kubernetes

• Experience with at least one major public cloud platform (GCP, AWS, Azure)

• Working knowledge of modern database technologies

• Proficiency with source control systems such as Git or Perforce

• Experience load testing, troubleshooting, and optimizing cloud service performance

• Ability to learn quickly and apply new technologies

• Bonus: Experience with animation systems or pipelines

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Your responsibilities will include researching, evaluating, and deploying Reinforcement Learning models and techniques for real-time applications, investigating novel imitation learning techniques applicable to the game's mechanics, and tailoring the functionality of these models and inference frameworks to fit FC's requirements and target platform constraints.

You will also develop, optimize, and polish game features that leverage these models to deliver them to FC players, share knowledge on your work by directly engaging with other members of the game team to develop and ship features, evangelize the craft through presentations and interactive demonstrations, promoting Machine Learning best practices and applications within the team, and stay abreast of the latest advancements in the Machine Learning and Reinforcement Learning field.

Required qualifications include a PhD or Masters degree in Computer Science, Mathematics, or a related field, or equivalent professional experience, strong computer programming fundamentals, proficiency in Python, and experience with C++. You should also have 5+ years of professional experience with ML, RL, and Imitation Learning along with their respective tools and frameworks, and a proven record of building, deploying, and maintaining Machine Learning applications in productized software.

Preferred qualifications include experience with deploying on-device RL systems, optimizing the RL loop for efficient training with complex environments, optimizing ML models for memory and compute constrained real-time environments, and working with cloud technology and platforms such as containers, Kubernetes, Azure, or AWS.

Electronic Arts offers a competitive salary range of $141,400 - $204,400 CAD per year, depending on location, and a comprehensive benefits package including vacation, sick time, paid parental leave, extended health and dental coverage, life insurance, disability insurance, and retirement plan.

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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.

About the Team

The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization.

About the Role

We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes early-access, systems/hardware, analyzing performance and bottlenecks, and characterizing the end-to-end behavior of new systems (compute, comms, storage, control plane, and failure modes).

Key Responsibilities

• Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar.

• Build a suite of benchmarks and stress tests that capture real E2E behavior of our workloads by exercising all aspects of a system, including CPU, GPU, memory subsystem, frontend, scale-up, and scale-out networking (including WAN traffic, NVlink and RDMA collectives), storage, thermals, and any other relevant parts.

• Deep-dive performance on distributed training/inference:

• Collective performance and tuning (across NCCL/RCCL and internal libraries)

• Overlap of compute/communication, kernel-level bottlenecks, memory bandwidth and scheduling effects

• Create repeatable test harnesses that run in CI / lab environments and produce actionable outputs (pass/fail, performance score, regression detection).

• Partner with systems + fleet bring-up engineers to ensure the platform is not only stable and performant, but also operationally usable and scalable (containerization, K8s integration, telemetry hooks, failure triage loops).

• Work cross-functionally with vendors and internal stakeholders by producing clear bug reports, minimal repros, and prioritized issue lists.

Qualifications

• BS in CS/EE (or equivalent practical experience).

• 5+ years in one or more of: ML systems, performance engineering, distributed systems, or HPC.

• Strong hands-on experience with:

• PyTorch and modern LLM training/inference stacks

• Large-scale distributed training concepts (data/model/pipeline parallel, collective comms)

• Experience with RDMA and debugging/optimizing comms libraries (NCCL or RCCL) and their interaction with hardware/network

• Proficiency in Python plus comfort reading/writing performance-critical code (C++/CUDA/HIP is a plus).

• Strong profiling/debugging skills (e.g., Nsight, rocprof, perf, flamegraphs; ability to reason from traces/counters).

Preferred Skills

• Experience building workload-shaped benchmarks and stress/fault tests that correlate to production behavior (not just synthetic loops or microbenchmarks).

• Familiarity with RDMA networking and transport tuning; understanding of how network topology and congestion impact collectives.

• Experience running and validating workloads in Kubernetes, and bridging “research code” into robust, repeatable infrastructure.

• Hands-on lab experience with early hardware (new NICs, new GPUs/accelerators, early racks).

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.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

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$380K – $555K • 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.

About the Team

The Foundations team focuses on how model behavior changes as we scale models, data, and compute. The team studies the interactions between model architecture, optimization, and training data, and uses those insights to guide how new models are designed and trained.

About the Role

In this role, you will build the systems that enable advanced AI models to run efficiently at scale. You will operate at the intersection of model research and systems engineering, translating new architectural ideas into high-performance inference systems that surface real tradeoffs in performance, memory, and scalability.

Your work will directly influence how models are designed, evaluated, and iterated on across the research organization. By developing and evolving high-performance inference infrastructure, you will enable researchers to explore new ideas with a clear understanding of their computational and systems implications.

This is not a product-serving role. Instead, it is a research-enabling systems role focused on performance, correctness, and realism - ensuring that AI research is grounded in what can actually scale.

In this role, you will:

• Design and build high-performance inference runtimes for large-scale AI models, with a focus on efficiency, reliability, and scalability.

• Own and optimize core execution paths, including model execution, memory management, batching, and scheduling.

• Develop and improve distributed inference across multiple GPUs, including parallelism strategies, communication patterns, and runtime coordination.

• Implement and optimize inference-critical operators and kernels informed by real-world workloads.

• Partner closely with research teams to ensure new model architectures are supported accurately and efficiently in inference systems.

• Diagnose and resolve performance bottlenecks through profiling, benchmarking, and low-level debugging.

• Contribute to observability, correctness, and reliability of large-scale AI systems.

You might thrive in this role if you:

• Have experience building production inference systems, not just training or running models.

• Are comfortable with GPU-centric performance engineering, including memory behavior and latency/throughput tradeoffs.

• Have worked on multi-GPU or distributed systems involving batching, scheduling, or runtime coordination.

• Can reason end-to-end about inference pipelines, from request handling through execution and output streaming.

• Are able to understand research ideas and implement them within real system and performance constraints.

• Enjoy solving hard, ambiguous systems problems that only emerge at scale.

• Prefer hands-on technical ownership and execution over abstract design work.

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.

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.

Required Skills

• Experience building production inference systems, not just training or running models

• Comfortable with GPU-centric performance engineering, including memory behavior and latency/throughput tradeoffs

• Multi-GPU or distributed systems involving batching, scheduling, or runtime coordination

• Reasoning end-to-end about inference pipelines, from request handling through execution and output streaming

• Understanding research ideas and implementing them within real system and performance constraints

• Solving hard, ambiguous systems problems that only emerge at scale

• Hands-on technical ownership and execution over abstract design work

Preferred Skills

• Experience working with large-scale AI models

• Distributed inference across multiple GPUs

• Parallelism strategies, communication patterns, and runtime coordination

• Implementing and optimizing inference-critical operators and kernels

• Observability, correctness, and reliability of large-scale AI systems

• 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

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Location: San Francisco

Department: Consumer Products

Job Type: Full time

Workplace Type: Hybrid

Compensation

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.

About the Team

The Future of Computing Research team is an applied research team in the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity.

About the Role

As a Technical Lead on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.

This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees.

In this role, you will:

• Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models.

• Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth.

• Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities.

• Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads.

• Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems.

• Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.

You might thrive in this role if you:

• Have experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators.

• Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements.

• Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines.

• Have experience building or leading teams working on low-level performance-critical software such as CUDA kernels, compilers, or ML runtimes.

• Have already spent time in the weeds teaching models to speak and perceive.

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.

Salary

Compensation Range: $445K

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We are a team of applied scientists working on machine learning components in the whole sponsored search stack. Our team works on problems related to machine learning, deep learning, natural language processing, multi-arm bandit, optimization, information retrieval, auction theory , among others. Our work entails building large-scale machine learning systems for ad matching, filtration, ranking, and multi objective optimization, and several other ML-driven business problems. You will design, implement, analyze, tune complex algorithms and ML systems and the supporting infrastructure for operating on large datasets. You will collaborate with top machine learning scientists and engineers in delivering direct business impact. We’re looking for sound understanding and insight into productionizing machine learning models in large-scale systems, an ability to pick up new technical areas, as well as a commitment to developing, delivering, and supporting algorithms in production.

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The ideal candidate will have a strong understanding of data warehousing fundamentals, SQL Server, and relational/dimensional database design. They will also possess excellent oral and written communication, presentation, and problem-solving skills. Experience working with large-scale data to build reporting solutions and knowledge of optimizing and performance tuning SQL and reports are highly desirable.

In addition to the above, the successful candidate will be a junior or senior in undergraduate studies, with a minimum of a bachelor's degree in a relevant field. They will be organized, positive, proactive, results-oriented, and able to work effectively in an open office/noisy environment.

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In this role, you will push the boundaries of container orchestration far beyond existing systems like Kubernetes, manage exascale compute resources, optimize for high-performance training runs and production serving, and collaborate closely with research and systems teams to deliver reliable, ultra-scalable infrastructure that enables xAI's next-generation models and applications.

Responsibilities include building and managing massive-scale clusters, designing, developing, and extending an in-house container orchestration platform, collaborating with research teams to architect and optimize compute clusters, profiling, debugging, and resolving complex system-level performance bottlenecks, and owning end-to-end infrastructure initiatives.

To succeed in this role, you will need deep expertise in virtualization technologies and advanced containerization/sandboxing, strong proficiency in systems programming languages such as C/C++ and Rust, and proven track record profiling, debugging, and optimizing complex system-level performance issues.

Preferred skills and experience include experience in Linux kernel development, hypervisor extensions, or low-level system programming for compute-intensive workloads, operating or designing large-scale AI training/inference clusters, and familiarity with performance tools, tracing, and debugging in production distributed environments.

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As a Senior Full-Stack Software Engineer on our Task Workflows Platform team, you will build and scale the foundational infrastructure that powers core experiences across Brex. You will work across our extensive suite of platforms - including our multi-channel notifications engine, collaborative commenting system, and dynamic workflow rule builder.

Responsibilities

• Work with engineers across the company to build new features and products end-to-end
• Own problems end-to-end, thinking through everything from user experience, data models, scalability, operability and ongoing metrics
• Provide technical leadership to team by driving roadmap direction, architectural design and mentorship
• Work side-by-side with user-facing teams (Sales, Support) to best understand the needs of our customers
• Tune and polish features to a high degree of excellence
• Identify and implement reliability and performance improvements
• Uphold our high engineering standards and bring consistency to the codebases, infrastructure, and processes you will encounter

Requirements

• 7+ years of professional experience designing, developing, and deploying full-stack products
• Strong proficiency in backend programming languages (Java, Kotlin, Python)
• Experience architecting, building, and maintaining scalable, high-availability distributed systems
• Experience designing and optimizing SQL and/or NoSQL databases, including data modeling, query performance tuning, and schema design
• Experience building and maintaining RESTful APIs and/or GraphQL services
• Experience with modern frontend technologies and tools like ES6+, React, TypeScript, and Webpack

Bonus points

• Experience collaborating with cross-functional stakeholders and specialists in product, design, and operations
• Experience driving initiatives at a broader level across an organization or company
• Experience running in-product experiments, A/B testing
• Experience and interest in leveraging AI developer tools

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors, including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

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You'll design intuitive, high-conversion journeys that turn curious users into loyal subscribers: optimizing discovery, pricing, checkout, onboarding, billing, upgrades/downgrades, retention nudges, and churn prevention.

You'll work closely with growth leads, engineers, researchers, and revenue stakeholders to turn complex business requirements into elegant, accessible, and delightful experiences that directly impact sign-ups, retention, expansion revenue, and lifetime value.

This is an excellent opportunity for a data-driven UX designer who combines deep user empathy, rigorous experimentation, systematic thinking, and hands-on design craft , and who loves both strategic growth discovery and pixel-perfect execution.

Responsibilities:

• Lead end-to-end Growth UX for subscription products and monetization features across web, mobile, and cross-platform surfaces

• Conduct targeted user research (funnel analysis, usability testing, interviews, surveys, A/B test deep-dives, contextual inquiry) focused on subscription decision points and translate insights into high-impact design decisions

• Create subscription-specific deliverables: user personas, journey maps, service blueprints, growth funnels, task flows, pricing & billing architecture

• Design and prototype high-conversion flows: discovery/pricing pages, checkout, account & billing management, upgrade paths, retention sequences, win-back experiences

• Collaborate daily with growth, product, and engineering teams to define requirements, technical constraints, experiment roadmaps, and prioritization

• Facilitate design critiques, growth workshops, and rapid alignment sessions with cross-functional stakeholders

• Operate in continuous discovery and delivery cycles (Agile/Lean) with a strong bias toward rapid experimentation and iteration

• Maintain and evolve design-system components for all subscription touchpoints in partnership with UI designers

• Measure and iteratively improve design impact using qualitative feedback + core growth metrics (subscription conversion rate, churn, upgrade/expansion revenue, LTV, task success, NPS/CSAT, funnel drop-off, etc.)

Basic Qualifications:

• 3–7+ years of professional UX design experience with a strong emphasis on growth UX, subscription products, SaaS monetization, or consumer subscription apps

• Strong portfolio demonstrating end-to-end ownership of shipped subscription/growth features , include case studies with clear problem statements, process, design decisions, experiments run, and quantifiable business outcomes (conversion lifts, churn reduction, revenue impact, etc.)

• Mastery of modern UX tools: Figma (primary), FigJam / Miro, and familiarity with at least one advanced prototyping tool beyond Figma (ProtoPie, Framer, Principle)

• Solid command of user-centered design principles, interaction patterns, accessibility (WCAG), and growth-design best practices (friction removal, progressive disclosure, personalization, loss aversion, etc.)

• Proven experience conducting and synthesizing qualitative + quantitative research, including funnel/deep-dive analysis and A/B test interpretation

• Excellent communication & storytelling skills , able to present and defend designs to non-designers using data and growth narratives

• Comfortable working in ambiguous, fast-moving environments with imperfect information and aggressive growth targets

Preferred Skills and Experience:

• Direct experience designing subscription experiences for consumer products

• Track record of optimizing pricing pages, checkout flows, billing portals, or churn-prevention sequences with measurable revenue impact

• Deep familiarity with experimentation frameworks (A/B testing, multivariate, bandit tests) and growth metric frameworks (AARRR / Pirate Metrics, North Star metrics, retention curves)

• Hands-on experience contributing to design systems and reusable subscription component libraries

• Previous exposure to front-end development basics (HTML/CSS, responsive behavior, design tokens)

• Background in service design, content strategy, or UX writing for monetization and retention touchpoints

Compensation and Benefits:

$120,000 - $280,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

ITAR Requirements:

To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

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At Cloudflare, we are on a mission to help build a better Internet. We run one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

As a Technical Support Engineer, you will work directly with our customers and cross-functionally to solve a variety of technical issues. This is a position where you will learn the inner workings of Cloudflare's products and gain a deeper understanding of internet technologies.

Responsibilities

Do you love solving complex technical problems and interacting with people? Are you passionate about helping customers and are a standout colleague? Cloudflare is seeking a Technical Customer Support Engineer to join our team.

You will work directly with our customers and cross-functionally to solve a variety of technical issues. This is a position where you will learn the inner workings of Cloudflare's products and gain a deeper understanding of internet technologies.

Requirements

• Experience: 2+ years of experience in a Technical Support role, Web Developer Support, or a similar position, with a proven track record of resolving diverse technical issues or foundational experience gained through a relevant degree and projects, internships, or academic coursework that demonstrates strong technical aptitude and problem-solving skills.

• Community Engagement: Active participation in web development communities, with a demonstrated commitment to staying current with industry trends and sharing knowledge with peers.

• Internet Fundamentals: Fundamental understanding of how the Internet works (OSI Model), with knowledge of Cloudflare's products that impact Layers 3, 4, and 7.

• Technical Proficiency: Skilled in analyzing and troubleshooting DNS, SSL/TLS, HTTP, and optimizing website performance.

• Tooling Expertise: Proficient in command line interfaces and experienced with tools such as browser developer tools, cURL, Git/Wrangler/npm, Postman, TCPDump/Wireshark, SSH, OpenSSL, and similar utilities.

• Video Technology: Experienced with video encoding and streaming solutions, understanding the associated technical challenges.

• Scripting Skills: Competent in writing scripts in Bash, Python, JavaScript, or other scripting languages.

• Customer-Centric Communication: Comfortable communicating through various support channels, with a strong commitment to putting the customer first in every interaction.

Bonus

• You have a site actively using our platform

• You are familiar with any of the following Cloudflare products: Cloudflare Workers, Stream, Pages, R2

Availability And Schedule Requirements

• Flexibility to work varying work schedules including; Pacific time, holidays, weekends, more than 5 days in a row, or additional hours

• Ability to work on-site as needed out of one of our US based offices

What Makes Cloudflare Special?

We're not just a highly ambitious, large-scale technology company. We're a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released.

Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you’d like to be a part of? We’d love to hear from you!

This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.

Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law.

We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

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Design and develop cybersecurity tools for real-time embedded, embedded Linux, and Android systems. Implement an endpoint detection and response agent for use on Anduril products. Develop thorough testing and qualification procedures for security-critical components. Collaborate with cross-functional teams to identify specific security needs and implement solutions. Conduct code reviews and ensure adherence to security best practices. Stay updated on the latest security threats and technologies.

Required qualifications include 2+ years of software development experience in Golang, Rust, or C/C++, experience with Linux observability and eBPF, strong understanding of Linux security internals, and experience debugging and optimizing performance of Linux software.

Preferred qualifications include knowledge of security frameworks and compliance standards, experience in mobile development, specifically on Android platforms, experience implementing EDR tooling, and experience with SOC operations, forensics, and incident response practices.

US Salary Range $166,000-$253,000 USD

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As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

To succeed on this team you will need to be curious, an excellent communicator, of a strong product mindset, be able to go from idea to implementation, and take ownership and pride in your work.

Propose, prototype, and deploy LLM-based agentic systems that help solve real-world problems, leveraging the latest state-of-the-art techniques in the field.

Work cross-functionally with different business lines across Anduril to help discover and scope new solutions.

Develop and maintain data pipelines, feature engineering workflows, and model-serving components that support applied AI use cases across the yard.

Learn and evangelize. You will be an expert on current AI technologies and trends (and their practical applications).

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

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About the Role:

When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe.

Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs.

More resources to learn about our work:

• Our research blog - covering advances including Monosemantic Features and Circuits

• An Introduction to Interpretability from our research lead, Chris Olah

• The Urgency of Interpretability from CEO Dario Amodei

• Engineering Challenges Scaling Interpretability - directly relevant to this role

• 60 Minutes segment - Around 8:07, see a demo of tooling our team built

• New Yorker article - what it's like to work on one of AI's hardest open problems

Even if you haven't worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model:

• Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips

• Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector"

• Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission

The science keeps scaling - and it's now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI.

Responsibilities:

• Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application

• Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams

• Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers

• Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations

• Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling

You may be a good fit if you:

• Have 5-10+ years of experience building software

• Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python

• Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks

• Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions

• Prefer fast-moving collaborative projects to extensive solo efforts

• Are curious about interpretability research and its role in AI safety (though no research experience is required!)

• Care about the societal impacts and ethics of your work

• Are comfortable working closely with researchers, translating research needs into engineering solutions.

Strong candidates may also have experience with:

• Optimizing the performance of large-scale distributed systems

• Language modeling fundamentals with transformers

• High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization

• Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs

• Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges

Representative Projects:

• Building Garcon, a tool that allows researchers to easily instrument LLMs to extract internal activations

• Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them

• Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization

• Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research)

Role Specific Location Policy:

• This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.

The annual compensation range for this role is listed below.

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

Annual Salary: $315,000-$560,000 USD

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You will work on projects that span technologies, systems, and processes where you will design, build, test, and ship great code every day. You will collaborate with multiple customers and stakeholders across Stripe to deliver value and debug production issues.

We're looking for someone with 2-12+ years of industry software engineering experience, who can write well-factored algorithms and has experience with commonly used data structures and algorithms. You should have hands-on experience contributing to or building large scale distributed systems, strong coding skills in any programming language, and strong collaboration skills.

Preferred qualifications include experience optimizing the end to end performance of distributed systems, focusing on the needs of our users, both internal and external, and holding yourself and others to a high bar when working with production.

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As a Research Engineer / Scientist on the Societal Impacts team, you'll design and build critical infrastructure that enables and accelerates foundational research into how our AI systems impact people and society.

Your work will directly contribute to our research publications, policy campaigns, safety systems, and products. Our team combines rigorous empirical methods with creative technical approaches. We’re currently grappling with big questions on how AI might impact the future of work, people's wellbeing, education, and more.

Additionally, we are continuously studying socio-technical alignment (what values do our systems have?), and evaluating novel AI capabilities as they arise. We develop privacy-preserving tools to measure AI's effects at scale, conduct mixed-methods studies of human-AI interaction, and translate research insights into actionable recommendations for both product and policy.

You can learn more about our team here

Responsibilities:

• Design and implement scalable technical infrastructure that enables researchers to efficiently run experiments and evaluate AI systems.
• Architect systems that can handle uncertain and changing requirements while maintaining high standards of reliability
• Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions
• Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission
• Interface with and improve our internal technical infrastructure and tools
• Generate net-new insights about the potential societal impact of systems being developed by Anthropic
• Ship changes that help improve our models and products based on the empirical research the Societal Impacts team is conducting

You may be a good fit if you:

• Have experience working with Research Scientists on ambiguous AI projects
• Have experience building and maintaining production-grade internal tools or research infrastructure
• Take pride in writing clean, well-documented code in Python that others can build upon
• Are comfortable making technical decisions with incomplete information while maintaining high engineering standards
• Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization
• Have a track record of using technical infrastructure to interface effectively with machine learning models
• Have experience deriving insights from imperfect data streams
• Have experience building systems and products on top of LLMs
• Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders

Strong candidates may also have experience with:

• Maintaining large, foundational infrastructure
• Building simple interfaces that allow non-technical collaborators to evaluate AI systems
• Working with and prioritizing requests from a wide variety of stakeholders, including research and product teams
• Distributed systems and can design for scale and reliability
• Scaling and optimizing the performance of tools
• Product management and/or full-stack product engineering, with a track record of zero-to-one work in startup (or startup-like environments) and owning products end-to-end
• Research relating to the societal impacts of technology

Representative Projects:

• Design, implement, and mature scalable infrastructure for running large-scale experiments on how people interact with our AI systems (like Clio, Anthropic Interviewer, the Economic Index, Values in the Wild, and Emotional Impacts).
• Build robust monitoring systems that help us detect and understand potential misuse or unexpected behaviors
• Create internal tools that help researchers, policy experts, and product teams quickly analyze dynamically changing AI system characteristics

Logistics

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

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You'll design intuitive, high-conversion journeys that turn curious users into loyal subscribers: optimizing discovery, pricing, checkout, onboarding, billing, upgrades/downgrades, retention nudges, and churn prevention.

You'll work closely with growth leads, engineers, researchers, and revenue stakeholders to turn complex business requirements into elegant, accessible, and delightful experiences that directly impact sign-ups, retention, expansion revenue, and lifetime value.

This is an excellent opportunity for a data-driven UX designer who combines deep user empathy, rigorous experimentation, systematic thinking, and hands-on design craft , and who loves both strategic growth discovery and pixel-perfect execution.

Responsibilities:

• Lead end-to-end Growth UX for subscription products and monetization features across web, mobile, and cross-platform surfaces

• Conduct targeted user research (funnel analysis, usability testing, interviews, surveys, A/B test deep-dives, contextual inquiry) focused on subscription decision points and translate insights into high-impact design decisions

• Create subscription-specific deliverables: user personas, journey maps, service blueprints, growth funnels, task flows, pricing & billing architecture

• Design and prototype high-conversion flows: discovery/pricing pages, checkout, account & billing management, upgrade paths, retention sequences, win-back experiences

• Collaborate daily with growth, product, and engineering teams to define requirements, technical constraints, experiment roadmaps, and prioritization

• Facilitate design critiques, growth workshops, and rapid alignment sessions with cross-functional stakeholders

• Operate in continuous discovery and delivery cycles (Agile/Lean) with a strong bias toward rapid experimentation and iteration

• Maintain and evolve design-system components for all subscription touchpoints in partnership with UI designers

• Measure and iteratively improve design impact using qualitative feedback + core growth metrics (subscription conversion rate, churn, upgrade/expansion revenue, LTV, task success, NPS/CSAT, funnel drop-off, etc.)

Basic Qualifications:

• 3–7+ years of professional UX design experience with a strong emphasis on growth UX, subscription products, SaaS monetization, or consumer subscription apps

• Strong portfolio demonstrating end-to-end ownership of shipped subscription/growth features , include case studies with clear problem statements, process, design decisions, experiments run, and quantifiable business outcomes (conversion lifts, churn reduction, revenue impact, etc.)

• Mastery of modern UX tools: Figma (primary), FigJam / Miro, and familiarity with at least one advanced prototyping tool beyond Figma (ProtoPie, Framer, Principle)

• Solid command of user-centered design principles, interaction patterns, accessibility (WCAG), and growth-design best practices (friction removal, progressive disclosure, personalization, loss aversion, etc.)

• Proven experience conducting and synthesizing qualitative + quantitative research, including funnel/deep-dive analysis and A/B test interpretation

• Excellent communication & storytelling skills , able to present and defend designs to non-designers using data and growth narratives

• Comfortable working in ambiguous, fast-moving environments with imperfect information and aggressive growth targets

Preferred Skills and Experience:

• Direct experience designing subscription experiences for consumer products

• Track record of optimizing pricing pages, checkout flows, billing portals, or churn-prevention sequences with measurable revenue impact

• Deep familiarity with experimentation frameworks (A/B testing, multivariate, bandit tests) and growth metric frameworks (AARRR / Pirate Metrics, North Star metrics, retention curves)

• Hands-on experience contributing to design systems and reusable subscription component libraries

• Previous exposure to front-end development basics (HTML/CSS, responsive behavior, design tokens)

• Background in service design, content strategy, or UX writing for monetization and retention touchpoints

Compensation and Benefits:

$120,000 - $280,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

ITAR Requirements:

To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

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In this role, you will work closely with clients to understand their objectives, recommend best practices, and develop effective advertising campaigns. You will also educate and consult clients on how to leverage our advertising products, sharing best practices to create and execute successful campaigns.

Responsibilities include executing, optimizing, and analyzing advertising programs using internal tools and dashboards to maximize performance and results. You will also resolve campaign issues promptly and effectively, identifying and implementing process improvements to enhance efficiency.

Additionally, you will manage contracts and renewals, supporting the Sales Finance team with payables and collections to ensure smooth operations. You will provide actionable feedback to product and tools teams to help scale and improve our advertising platform.

This is an in-person role based in Tokyo, JP.

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Cyngn is a publicly-traded autonomous technology company that deploys self-driving industrial vehicles to factories, warehouses, and other facilities throughout North America.

We are a small company with under 100 employees, operating with the energy of a startup. However, we're also publicly traded, which means our employees get access to the liquidity of our publicly-traded equity.

As a Senior DevOps Lead at Cyngn, you will play a vital role in architecting and managing infrastructure across cloud and autonomous vehicle systems. This position combines traditional cloud DevOps leadership with specialized expertise in robotics and autonomous systems infrastructure.

Responsibilities

• Lead and architect cloud and vehicle infrastructure initiatives across AWS and ROS/Linux environments
• Design and implement scalable solutions for both cloud services and autonomous vehicle systems
• Establish and maintain DevOps best practices, CI/CD pipelines, and infrastructure as code
• Drive observability, monitoring, and incident response strategies
• Optimize performance and cost efficiency of cloud and edge computing resources
• Mentor team members and foster a developer-friendly environment
• Manage on-call rotations and incident response processes
• Architect solutions for processing and storing large-scale vehicle telemetry data
• Lead security initiatives and compliance efforts across infrastructure

Requirements

• 10+ years of relevant DevOps/Infrastructure experience
• Proven track record as a technical lead in platform or infrastructure teams
• Advanced expertise in AWS services, infrastructure as code (Terraform), and Kubernetes
• Strong experience with service mesh (Istio) and Helm/Kustomize
• Deep understanding of ROS/ROS2 and Linux kernel configurations
• Experience with GPU configurations and ML infrastructure
• Expertise in ARM and NVIDIA CUDA platform configurations
• Strong programming skills in Python and shell scripting
• Experience with infrastructure automation (Ansible)
• Expertise in CI/CD tools (Jenkins, GitHub Actions)
• Strong system architecture and design skills
• Excellence in technical documentation
• Outstanding problem-solving abilities
• Strong leadership and mentoring capabilities

Nice to haves

• Experience with autonomous vehicle systems
• Track record of optimizing GPU-based ML infrastructure
• Experience with large-scale IoT deployments
• Contributions to open-source projects
• Experience with real-time systems and low-latency requirements
• Expertise in security implementations including SSO, IdP, and AWS Cognito
• Experience with JFrog artifactory and container registry management
• Proficiency in AWS IoT Greengrass
• Experience with container resource management on edge devices
• Understanding of CPU affinity and priority scheduling
• Track record of implementing cost optimization strategies
• Experience with scaling systems both horizontally and vertically

Benefits & Perks

• Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)
• Life, Short-term, and long-term disability insurance (Cyngn funds 100% of premiums)
• Company 401(k)
• Commuter Benefits
• Flexible vacation policy
• Sabbatical leave opportunity after five years with the company
• Paid Parental Leave
• Daily lunches for in-office employees
• Monthly meal and tech allowances for remote employees

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Member of Technical Staff - Image / Video Generation

Job Description

We're the team behind Latent Diffusion, Stable Diffusion, and FLUX,foundational technologies that changed how the world creates images and video. We're creating the generative models that power how people make images and video,tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we’re just getting started.

Why This Role

You'll train large-scale diffusion models for image and video generation, exploring new approaches while maintaining the rigor that helps us distinguish meaningful progress from incremental tweaks. This isn't about following established recipes,it's about running the experiments that clarify which architectural choices matter and which are less impactful.

What You’ll Work On

• Trains large-scale diffusion transformer models for image and video data, working at the scale where intuitions break and empirical evidence matters
• Rigorously ablates design choices,running experiments that isolate variables, control for confounds, and produce insights you can actually trust,then communicating those results to shape our research direction
• Reasons about the speed-quality tradeoffs of neural network architectures in production settings where both constraints matter simultaneously
• Fine-tunes diffusion models for specialized applications like image and video upscalers, inpainting/outpainting models, and other tasks where general-purpose models aren't enough

What We’re Looking For

• You've trained large-scale diffusion models and developed strong intuitions about what matters. You know that at research scale, every design choice has tradeoffs, and the only way to know which ones are worth making is through careful ablation. You're comfortable debugging distributed training issues and presenting research findings to the team.

Required Skills

• Hands-on experience training large-scale diffusion models for image and video data, with practical knowledge of common failure modes and what matters most in training
• Experience fine-tuning diffusion models for specialized applications,upscalers, inpainting, outpainting, or other tasks where understanding the domain matters as much as understanding the architecture
• Deep understanding of how to effectively evaluate image and video generative models,knowing which metrics correlate with quality and which are just convenient proxies
• Strong proficiency in PyTorch, transformer architectures, and the full ecosystem of modern deep learning
• Solid understanding of distributed training techniques,FSDP, low precision training, model parallelism,because our models don't fit on one GPU and training decisions impact research outcomes

Preferred Skills

• Experience writing forward and backward Triton kernels and ensuring their correctness while considering floating point errors
• Proficiency with profiling, debugging, and optimizing single and multi-GPU operations using tools like Nsight or stack trace viewers
• Know the performance characteristics of different architectural choices at scale
• Have published research that contributed to how people think about generative models

How We Work Together

We’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process.

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Responsibilities:

• Build a great customer experience for internal and external Stripe teams using our infrastructure
• Participate in roadmap planning and prioritization
• Deliver value through a strong collaborative approach with multiple customers and stakeholders across Stripe
• Debug production issues across services and several levels of the stack

Requirements:

• 4-12+ years of industry software engineering experience
• Ability to write well-factored algorithms and have experience with commonly used data structures and algorithms
• Hands-on experience contributing to or building large scale distributed systems
• Strong coding skills in any programming language
• Strong collaboration skills, can work across workstreams within your team and contribute to your peers' success
• Have the ability to thrive on a high level of autonomy, responsibility, and think of yourself as entrepreneurial
• Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users

Preferred Qualifications:

• Experience optimizing the end to end performance of distributed systems
• Focuses on the needs of our users, both internal and external
• Hold yourself and others to a high bar when working with production

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In this role, you will collaborate closely with sales and pre-sales teams to drive pipeline and revenue targets, while also educating the product and engineering teams on market trends and influencing the product roadmap. You will develop deep relationships with senior customer business leaders and grow Stripe's solution offerings with new and existing customers.

Responsibilities include leading customer teams to visualize, strategize, prioritize, implement, and measure impact and growth with Stripe solutions, partnering with customers to co-develop a strategy to embed our Payments capabilities and experiences throughout their platform, and working with business and technology leaders to understand the holistic business strategy and define solution-specific architectures.

To succeed in this role, you will need 7+ years of experience working in payments, fintech, or a related industry, knowledge of ISO payment standards, and experience with designing payment flows and architectures for large enterprises. You should also have a strong understanding of the impact of optimizing payment experiences for checkout conversion and be able to consult on the best design options for accepting payments.

Approximately 25% travel is anticipated to help you connect in-person with users and collaborate internally.

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We're looking for a talented Backend Engineer to join our Core Tech team in Canada. As a Backend Engineer, you will work on projects that span technologies, systems, and processes, designing, building, testing, and shipping great code every day.

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies,from the world’s largest enterprises to the most ambitious startups,use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.

Our Mission

Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the Organisation

Stripe Infrastructure is responsible for the reliability, scale, performance, and cost of Stripe’s systems and the productivity and sentiment of Stripe’s people.

Responsibilities

• Build a great customer experience for internal and external Stripe teams using our infrastructure
• Participate in roadmap planning and prioritization
• Deliver value through a strong collaborative approach with multiple customers and stakeholders across Stripe
• Debug production issues across services and several levels of the stack

Who You Are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum Requirements

• Strong software engineering skills and a passion for one of the areas above
• Ability to write high quality code (in programming languages like Go, Java, C/C++ etc)
• 2-12+ years of professional hands-on software development experience, able to write well-factored algorithms and have experience with commonly used data structure and algorithms
• Hands-on experience contributing to or building large scale distributed systems
• Strong collaboration skills, can work across workstreams within your team and contribute to your peers’ success
• Customer obsession, ability to articulate and represent customer experience in various forums to drive the right outcome
• Have the ability to thrive on a high level of autonomy, responsibility, and think of yourself as entrepreneurial

Preferred Qualifications

• Experience optimizing the end to end performance of distributed systems
• Focuses on the needs of our users, both internal and external
• Holds yourself and others to a high bar when working with production

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Responsibilities:

• Lead the development of next Gen Advanced Driver Assistance Systems (ADAS) simulation environment using C++
• Develop ADAS simulation methods, processes, tools and documentation to integrate multiple ADAS features to support feature design, verification and validation
• Manage the deployment and release of the next Gen ADAS simulation environments on CI/CD pipeline to test ADAS software on every code change
• Support the integration of vehicle, sensor and feature control models and software to support the delivery of ADAS features
• Support on-going CAE correlations efforts
• Support the development of plan to transition physical vehicle testing to simulation-based tests
• Contribute to team results through ownership in agile software development process

Qualifications:

• B.S. in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechatronics or a related field or a combination of education and equivalent experience
• 3+ years of experience with programming in C++ (11 or above), Python or other Object-Oriented Programming (OOP) languages in Windows or Linux environments

Our Preferred requirements:

• M.S. in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechatronics or a related field
• 3+ years of Experience with Linux or other POSIX Operating Systems
• 3+ years of Experience with networking (TCP/IP)
• 3+ years of developing software using modern development tools like Bazel, Docker, Git, GitHub Actions, Kubernetes, and Jenkins
• 3+ years of developing software on Cloud platforms like Google Cloud, AWS or Azure
• 8+ or more years of relevant experience in software design, including debugging, performance analysis, and automation of testing designs
• Experience developing platforms or tools for internal customers.
• Experience with AI, cloud, simulation, accelerated computing, and Python ecosystem
• Experience with optimizing large scale software architecture through concurrency or GPU technology
• Experience with Robot Operating System (ROS) or other middleware
• Experience with vehicle systems and their role in ADAS simulation

Benefits:

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.

Salary:

This position is a salary grade 6 through 8 and ranges from $83,000 to $160.000.

Workplace:

This position is a hybrid (onsite four days per week) for candidates who are in commuting distance to a Ford hub location.

Job Info:

• Job Identification59584
• Job CategoryPD Operations and Quality
• Posting Date03/05/2026, 07:01 PM
• Degree LevelBachelor's Degree or equivalent
• Job ScheduleFull time
• Locations1200 Sawgrass Corporate Pkwy, Sunrise, FL, 33323, US(Hybrid)
• Preferred DegreeMaster Degree
• RemoteNo

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Our team combines rigorous empirical methods with creative technical approaches. We’re currently grappling with big questions on how AI might impact the future of work, people's wellbeing, education, and more. Additionally, we are continuously studying socio-technical alignment (what values do our systems have?), and evaluating novel AI capabilities as they arise. We develop privacy-preserving tools to measure AI's effects at scale, conduct mixed-methods studies of human-AI interaction, and translate research insights into actionable recommendations for both product and policy.

Strong candidates will have a track record of running & designing experiments relating to machine learning systems, building data processing pipelines, architecting & implementing high-quality internal infrastructure, working in a fast-paced startup environment, navigating the ambiguity inherent to novel empirical research, and demonstrating an eagerness to develop their own research & technical skills. The ideal candidate will enjoy a mixture of running experiments, developing new tools & evaluation suites, working cross-functionally across multiple research and product teams, and striving for beneficial & safe uses for AI.

For this role, we are open to a 6-month residency at Anthropic with the expectation that residents convert to full-time if they do well in their residency. In addition, we are exclusively hiring in SF. We support relocation, but all hires must relocate before starting.

Responsibilities:

• Design and implement scalable technical infrastructure that enables researchers to efficiently run experiments and evaluate AI systems.
• Architect systems that can handle uncertain and changing requirements while maintaining high standards of reliability
• Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions
• Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission
• Interface with and improve our internal technical infrastructure and tools
• Generate net-new insights about the potential societal impact of systems being developed by Anthropic
• Ship changes that help improve our models and products based on the empirical research the Societal Impacts team is conducting

You may be a good fit if you:

• Have experience working with Research Scientists on ambiguous AI projects
• Have experience building and maintaining production-grade internal tools or research infrastructure
• Take pride in writing clean, well-documented code in Python that others can build upon
• Are comfortable making technical decisions with incomplete information while maintaining high engineering standards
• Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization
• Have a track record of using technical infrastructure to interface effectively with machine learning models
• Have experience deriving insights from imperfect data streams
• Have experience building systems and products on top of LLMs
• Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders

Strong candidates may also have experience with:

• Maintaining large, foundational infrastructure
• Building simple interfaces that allow non-technical collaborators to evaluate AI systems
• Working with and prioritizing requests from a wide variety of stakeholders, including research and product teams
• Distributed systems and can design for scale and reliability
• Scaling and optimizing the performance of tools
• Product management and/or full-stack product engineering, with a track record of zero-to-one work in startup (or startup-like environments) and owning products end-to-end
• Research relating to the societal impacts of technology

Representative Projects:

• Design, implement, and mature scalable infrastructure for running large-scale experiments on how people interact with our AI systems (like Clio, Anthropic Interviewer, the Economic Index, Values in the Wild, and Emotional Impacts).
• Build robust monitoring systems that help us detect and understand potential misuse or unexpected behaviors
• Create internal tools that help researchers, policy experts, and product teams quickly analyze dynamically changing AI system characteristics

The annual compensation range for this role is listed below.

Annual Salary:

$350,000 - $500,000USD

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San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $266K – $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.

• 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

OpenAI’s Hardware team designs the custom silicon that powers the world’s most advanced AI systems. From system-level architecture to custom circuit implementations, we partner closely with model and infrastructure teams to deliver performance, power, and efficiency breakthroughs across all layers of the stack.

About the Role

We are seeking a highly skilled Silicon Implementation Engineer with deep expertise in physical design and methodology. This individual contributor role sits within our physical design team and is central to delivering power, performance, and area (PPA) optimized datapath and interconnect solutions for next-generation AI accelerators.

You’ll work closely with RTL designers to define and execute on physical design strategies. You will develop tools, flows and methodologies to increase team productivity. Your work will directly impact silicon’s performance and cost efficiency, as well as the team’s execution velocity and quality.

In this role, you will:

• Develop, build and own tools, flows and methodologies for physical implementation
• Own physical implementation of floorplan blocks from floorplanning to final signoff
• Collaborate with RTL designers to drive optimal block implementation solutions
• Analyze and optimize design for timing, power, and area trade-offs, working in collaboration with EDA vendors and ASIC partners

Qualifications:

• BS w/ 4+ or MS with 2+ years or PhD with 0-1 year(s) of relevant industry experience in physical design and methodology development
• Demonstrated success in taping out complex silicon designs
• Hands-on experience with block physical implementation and PPA convergence
• Strong coding experience with python, bazel, TCL
• Strong experience building physical design tools, flows and methodologies
• Strong understanding of microarchitecture, RTL design, physical design, circuit design, physical verification and timing closure.
• Deep familiarity with industry-standard tools and flows for physical synthesis, PNR, LEC and power estimation

Bonus:

• Experience with AI or HPC-focused chips
• Experience with optimizing PPA for high performance compute cores
• Hands-on experience with top-level design methodologies

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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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.

• 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

The Alignment team at OpenAI is dedicated to ensuring that our AI systems are safe, trustworthy, and consistently aligned with human values, even as they scale in complexity and capability. Our work is at the cutting edge of AI research, focusing on developing methodologies that enable AI to robustly follow human intent across a wide range of scenarios, including those that are adversarial or high-stakes. We concentrate on the most pressing challenges, ensuring our work addresses areas where AI could have the most significant consequences. By focusing on risks that we can quantify and where our efforts can make a tangible difference, we aim to ensure that our models are ready for the complex, real-world environments in which they will be deployed.

The two pillars of our approach are: (1) harnessing improved capabilities into alignment, making sure that our alignment techniques improve, rather than break, as capabilities grow, and (2) centering humans by developing mechanisms and interfaces that enable humans to both express their intent and to effectively supervise and control AIs, even in highly complex situations.

About the Role

As a Research Engineer / Research Scientist on the Alignment team, you will be at the forefront of ensuring that our AI systems consistently follow human intent, even in complex and unpredictable scenarios. Your role will involve designing and implementing scalable solutions that ensure the alignment of AI as their capabilities grow and that integrate human oversight into AI decision-making.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

We are seeking research engineers and research scientists to help design and implement experiments for alignment research. Responsibilities may include:

• Develop and evaluate alignment capabilities that are subjective, context-dependent, and hard to measure.
• Design evaluations to reliably measure risks and alignment with human intent and values.
• Build tools and evaluations to study and test model robustness in different situations.
• Design experiments to understand laws for how alignment scales as a function of compute, data, lengths of context and action, as well as resources of adversaries.
• Design and evaluate new Human-AI-interaction paradigms and scalable oversight methods that redefine how humans interact with, understand, and supervise our models.
• Train model to be calibrated on correctness and risk.
• Designing novel approaches for using AI in alignment research

You might thrive in this role if you:

• Are a team player – willing to do a variety of tasks that move the team forward.
• Have a PhD or equivalent experience in research in computer science, computational science, data science, cognitive science, or similar fields.
• Have strong engineering skills, particularly in designing and optimizing large-scale machine learning systems(e.g., PyTorch).
• Have a deep understanding of the science behind alignment algorithms and techniques.
• Can develop data visualization or data collection interfaces (e.g., TypeScript, Python).
• Enjoy fast-paced, collaborative, and cutting-edge research environments.
• Want to focus on developing AI models that are trustworthy, safe, and reliable, especially in high-stakes scenarios.

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 of our team members, partners, and users.

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San Francisco

Employment Type

Full time

Department

Research

Compensation

• $293K – $490K • 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

The Sora team is working on making video a key capability of OpenAI’s foundation models. We are a hybrid research and product team that seeks to understand and expand the capabilities of our video models, while ensuring their reliability and safety. We accomplish this both through directly studying and experimenting with the models, as well as deploying them into the real-world to distribute their benefits widely.

About the Role

As a Distributed Systems/ML engineer, you will work on improving the training throughput for our internal training framework and enable researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Collaborate with researchers to enable them to develop systems-efficient video models and architectures
• Apply the latest techniques to our internal training framework to achieve impressive hardware efficiency for our training runs
• Profile and optimize our training framework

You might thrive in this role if you:

• Have experience working with multi-modal ML pipelines
• Love diving deep into systems implementations and understanding their fundamentals in order to improve their performance and maintainability
• Have strong software engineering skills and are proficient in Python.
• Have experience understanding and optimizing training kernels
• Are passionate about understanding stable training dynamics

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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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $295K – $555K • 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 Team

Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference.

About the Role

We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment.

In this role, you will:

• Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production.

• Work alongside researchers to enable advanced research through awesome engineering.

• Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack.

• Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

• Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware.

You might thrive in this role if you:

• Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference.

• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.

• Have at least 5 years of professional software engineering experience.

• Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc.

• Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems.

• Have needed to rebuild or substantially refactor production systems several times over due to rapidly increasing scale.

• Are self-directed and enjoy figuring out the most important problem to work on.

• Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed.

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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Microsoft AI are looking for a talented Member of Technical Staff, LLM Inference to join their MAI Superintelligence Team in New York. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI research and development. You'll work directly with leadership to shape the company's direction in the AI and machine learning markets.

About the Role

Our Inference team is responsible for building and maintaining the tools and systems that enable Microsoft AI researchers to run models easily and efficiently. Our work empowers researchers to run models in RL, synthetic data generation, evals, and more. We are joint stewards of one of the largest compute fleets in the world. The team is responsible for optimizing compute efficiency on our heterogeneous data centers as well as enabling cutting-edge research and production deployment. We are an applied research team that is embedded directly in Microsoft AI’s research org to work as closely as possible with researchers. We are vertically integrated, owning everything from kernels to architecture co-design to distributed systems to profiling and testing tools.

Accountabilities

• Work alongside researchers and engineers to implement frontier AI research ideas.
• Introduce new systems, tools, and techniques to improve model inference performance.
• Build tools to help debug performance bottlenecks, numeric instabilities, and distributed systems issues.
• Build tools and establish processes to enhance the team’s collective productivity.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Technical skills:

• Experience with generative AI.
• Experience with distributed computing.
• Python and Python ecosystem (eg. uv, pybind/nanobind, FastAPI) expertise.

Personal attributes:

• Results-oriented, have a bias toward action, and enjoy owning problems end-to-end.
• Embody our Culture and Values.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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Microsoft AI are looking for a talented Member of Technical Staff, LLM Inference to join their team in Redmond. This role will involve working alongside researchers and engineers to implement frontier AI research ideas and introduce new systems, tools, and techniques to improve model inference performance.

About the Role

As a Member of Technical Staff, LLM Inference, you will be responsible for building and maintaining the tools and systems that enable Microsoft AI researchers to run models easily and efficiently. This will involve working on a variety of tasks, including building tools to help debug performance bottlenecks, numeric instabilities, and distributed systems issues. You will also be responsible for building tools and establishing processes to enhance the team's collective productivity.

Accountabilities

• Work alongside researchers and engineers to implement frontier AI research ideas
• Introduce new systems, tools, and techniques to improve model inference performance
• Build tools to help debug performance bottlenecks, numeric instabilities, and distributed systems issues
• Build tools and establish processes to enhance the team's collective productivity

The Candidate we're looking for

Experience:

• 6+ years of technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

Technical skills:

• Experience with generative AI
• Experience with distributed computing
• Python and Python ecosystem (eg. uv, pybind/nanobind, FastAPI) expertise

Personal attributes:

• Results-oriented, have a bias toward action, and enjoy owning problems end-to-end

Benefits

• Competitive salary
• Comprehensive benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment

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Microsoft AI are looking for a talented Member of Technical Staff, LLM Inference to join their MAI Superintelligence Team. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI research and development. You'll work directly with leadership to shape the company's direction in the AI and machine learning markets.

About the Role

Our Inference team is responsible for building and maintaining the tools and systems that enable Microsoft AI researchers to run models easily and efficiently. Our work empowers researchers to run models in RL, synthetic data generation, evals, and more. We are joint stewards of one of the largest compute fleets in the world. The team is responsible for optimizing compute efficiency on our heterogeneous data centers as well as enabling cutting-edge research and production deployment. We are an applied research team that is embedded directly in Microsoft AI’s research org to work as closely as possible with researchers. We are vertically integrated, owning everything from kernels to architecture co-design to distributed systems to profiling and testing tools.

Accountabilities

• Work alongside researchers and engineers to implement frontier AI research ideas.
• Introduce new systems, tools, and techniques to improve model inference performance.
• Build tools to help debug performance bottlenecks, numeric instabilities, and distributed systems issues.
• Build tools and establish processes to enhance the team’s collective productivity.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Technical skills:

• Experience with generative AI.
• Experience with distributed computing.
• Python and Python ecosystem (eg. uv, pybind/nanobind, FastAPI) expertise.

Personal attributes:

• Results-oriented, have a bias toward action, and enjoy owning problems end-to-end.
• Value clear communication, improving team processes, and being a supportive team player.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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Microsoft AI are looking for a talented Member of Technical Staff - Engineering Manager, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Member of Technical Staff - Engineering Manager, you will build and lead a team of backend and machine learning engineers, including driving project planning, prioritization of work, and designing features. You will guide teams and leads identification of dependencies and the development of design documents for a product, application, service, or platform. You will make hands-on contributions to the codebase and infrastructure. You will guide architecture and design efforts by leading discussions, creating proposals and design documents, and ensuring solutions meet business, security, and compliance requirements. You will ship AI powered experiences that will shape how millions of people will interact with AI in the future. You will drive implementation of features and systems, breaking down long-term goals into clear milestones, aligning with release plans, and ensuring cross-team coordination.

Accountabilities

• Build and lead a team of backend and machine learning engineers, including driving project planning, prioritization of work, and designing features.
• Guide teams and leads identification of dependencies and the development of design documents for a product, application, service, or platform.

The Candidate we're looking for

Experience:

• 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Proven experience building large-scale distributed systems and optimizing workloads for efficiency and scalability.
• Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies in AI.

Personal attributes:

• Strong leadership and management skills.
• Excellent communication and collaboration skills.

Benefits

• Competitive salary.
• Comprehensive benefits package.
• Opportunities for professional growth and development.

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What you'll do

• Research and evaluate machine learning models across areas such as automatic speech recognition, natural language processing, and procedural content generation.
• Adapt and optimize models to meet gameplay requirements and platform constraints and integrate them into core game systems.

What you need

• Strong programming fundamentals with proficiency in at least one language (C++, Python, Java, or C# preferred).

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What you'll do

We are looking for a Senior Data Engineer to lead the technical initiatives for AI Data Engineering, enabling scalable, high-performance data pipelines that power AI and machine learning applications. This role will focus on architecting, optimizing, and managing data infrastructure to support AI model training, feature engineering, and real-time inference. You will collaborate closely with AI/ML engineers, data scientists, and platform teams to build the next generation of AI-driven products.

• Lead AI Data Engineering initiatives by driving the design and development of robust data pipelines for AI/ML workloads, ensuring efficiency, scalability, and reliability.
• Design and implement data architectures that support AI model training, including feature stores, vector databases, and real-time streaming solutions.
• Develop high performance data pipelines that process structured, semi-structured, and unstructured data at scale, supporting the various AI applications

What you need

• Hands on experience working with Vector/Graph;Neo4j
• 3+ years of experience in data engineering, working on AI/ML-driven data architectures

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