Software Engineer Ml Infrastructure Platform in United States

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! 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. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a member of the Infrastructure Foundation Hardware Engineering team, you will play a key role in enabling our mission to deliver a reliable, high-performing, and cost-efficient infrastructure that powers the world’s play. In this specialized role, you will be the technical lead for our GPU and AI accelerator ecosystem. You will be responsible for the full lifecycle of GPU hardware, from initial architectural evaluation and firmware qualification to large-scale fleet integration and performance tuning. You will ensure that Roblox’s massive-scale rendering and ML workloads run on the most optimized and stable hardware possible. You Will: Architect & Prototype: Prototype next-generation GPU-accelerated hardware platforms, ensuring seamless integration between high-density compute nodes, high-speed interconnects (NVLink/PCIe Gen5/6), and system firmware. GPU Optimization: Drive the integration, performance testing, and debugging of GPUs in our fleet, focusing specifically on hardware-level optimizations, driver tuning, and thermal/power management. Validation & Certification: Develop and execute rigorous evaluation and stress-testing strategies for GPU-heavy server platforms to ensur

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The AI Platform Engineer builds and operates the machine learning and generative AI platform used by teams across Abbott Cancer Diagnostics. You'll own the full model lifecycle in production — data and feature pipelines, training and experimentation, evaluation and promotion, serving, and monitoring — along with the platform services, compute and tooling underneath it. This is hands-on infrastructure work backed by solid platform engineering practice: making inference fast and cheap, making the path from experiment to production repeatable and auditable, and shipping interfaces other engineers can build on — in support of software that ultimately reaches patients. Essential Duties Include, but are not limited to, the following: Build and maintain data, feature, and training pipelines for ML and LLM workloads — ingestion, transformation, fine-tuning, distributed training, and reproducible experiment execution with lineage tracked from dataset and code to resulting model. Implement automated evaluation and promotion gates — performance benchmarks, regression checks, and validation criteria that determine whether a model advances toward production. Automate the model lifecycle end to end through CI/CD and GitOps: packaging, promotion across environments, progressive rollout, and rollback. Build and operate production model-serving infrastructure for LLMs and predictive models, including inference optimization, autoscaling,

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox , we’re building the tools and platform that empower a global community of creators and developers to build immersive experiences and a dynamic virtual economy. Our Economy ML team sits at the heart of this mission, delivering scalable machine learning systems that power personalization, pricing, search, and content understanding across all Economy surfaces: Marketplace, Developer Monetization, Payments, and Avatar. We’re looking for a Distinguished Engineer/Technical Director to lead the strategy and technical direction for ML systems , with a focus on large-scale recommendations, infrastructure, and emerging Generative AI applications. You’ll help build the systems that support retrieval, ranking, generative modeling, and LLM-powered personalization, all at massive scale. This role requires deep systems thinking, hands-on ML expertise, and a vision for how traditional ML and GenAI come together to power the future of the Roblox economy. Why Roblox for ML Systems AI/ML is a top company priority , with long-term investment. Real-world scale : Power millions of daily economic interactions across ranking, pricing, fraud, and search. Full-system ownership : Build and optimize end-to-

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect

About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role OpenAI is developing custom silicon to power the next generation of frontier AI models. We’re looking for experienced Design Verification (DV) Engineers to ensure functional correctness and robust design for our cutting-edge ML accelerators. You will play a key role in verifying complex hardware systems—ranging from individual IP blocks to subsystems and full SoC—working closely with architecture, RTL, software, and systems teams to deliver reliable silicon at scale. In this role you will: Own the verification of one or more of: custom IP blocks, subsystems (compute, interconnect, memory, etc.), or full-chip SoC-level functionality. Define verification plans based on architecture and microarchitecture specs. Develop constrained-random, directed, and system-level testbenches using SystemVerilog/UVM or equivalent methodologies. Build and maintain stimulus generators, checkers, monitors, and scoreboards to ensure high coverage and correctness. Drive bug triage, root cause analysis, and work closely with design teams on resolution. Contribute to regression infrastructure, coverage analysis, and closure for both block- and top-level environments. You might thrive in this role if you have: BS/MS in EE/CE/CS or equivalent with 3+ years of experience in hardware verification. Proven success verifying complex IP or SoC designs in industry-standard flows Proficient in SystemVerilog, UVM, and common simulation and debug tools (e.g., VCS, Questa, Verdi). Strong knowledge

Principal Embedded SW/FW Engineer (Bringup) - Austin, Tx, USA Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential: Understanding of ML

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. Drive customer impact by designing, implementin

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. Drive customer impact by designing, implementin

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. With Roblox Ads business growing at a rapid rate, we are building large scale ads machine learning infrastructure to deliver effective performance ads to our users, and more business values to our advertisers. We’re looking for an EM to lead a team of exceptional ML infrastructure engineers, build scalable, reliable, and high-performance infrastructure that powers ML systems across our organization. You’ll operate at the scales of hundreds of billions of engagements, and redefine how we deliver performance ads to hundreds of millions of users. You Will: Lead strategic planning and roadmap execution of scalable production-ready ML systems including model training, data pipelines, feature engineering and model inference. Own the architecture, establish engineering best practices of scalability, reliability, and cost-effectiveness of ML infrastructure (e.g., training, serving, feature). Work closely with data scientists, ML engineers, platform teams, and product stakeholders to design, implement, and operate robust ML platforms that accelerate model development and deployment. Recruit, mentor, and grow a high-performing team of ML infrastructure engineers. You Have: 5+ years of experienc

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Conversion Visibility Modeling team enables a performant ads marketplace and helps prove value to advertisers by connecting Pinterest onsite activity with conversions that happen offsite (both digital and physical) in a privacy-preserving way. As a Machine Learning Engineering Manager on this team, you will lead a hybrid team of ML engineers and backend software engineers to build end-to-end identity and conversion visibility solutions across modeling, serving, and data infrastructure, so advertisers retain accurate, privacy-aware performance visibility as signals fragment and degrade. You will set the technical direction for high-impact ML systems that feed ranking, bidding, measurement, and reporting across Pinterest’s ads stack. What you’ll do: Attract, hire, develop, and lead a hybrid team of ML engineers and backend softwar

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Media Foundation team builds the core platforms and infrastructure that power photo and video capture, upload, processing, storage, and delivery across Airbnb's products, at a massive global scale. We partner closely with Product, Design, Data Science, Trust, and Infrastructure teams to ensure every image and video guests and Hosts see is fast, high-quality, and reliable, from the moment a Host uploads a photo to the moment a Guest views it in search results. The Difference You Will Make: As the Senior Engineering Manager for Media Foundation, you will lead a team of engineers to build and operate Airbnb's media infrastructure, the foundation powering every photo, video, and document that users interact with on the platform. Capabilities include uploads, AI/ML transformations, distribution, and presentation within the product. You will shape the team’s vision and help steer the organization towards our larger goals. This includes day-to-day operations, technical deep dives, community engagement with internal engineering teams, and strategic planning. As the technical and organizational leader for Media Foundation, you own the reliability, scalability, and evolution of the systems that power every media interaction on the Airbnb platform from the moment a host uploads a photo to the instant a guest streams a listing video. Your experience in both media technology and people management will be essential to the maintenance, modernization, and innovation of Airbnb's media platform. You set the bar for engineering excellence, define what great looks like for your team, and crea

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Senior Software Engineer, ML Systems & Training Infrastructure, you will be a deeply hands-on engineering force multiplier for the robotics team. You will help keep the training framework and surrounding infrastructure healthy, review and improve code quickly, debug failures across ML systems and infrastructure, and unblock researchers and engineers when the path from idea to working training job gets rough. We’re looking for people who love writing, reading, reviewing, and fixing code; who can get productive quickly in unfamiliar systems; and who bring strong practical judgment without a lot of ego or process overhead. This role will be based in San Francisco, CA and be expected in office 5 days per week and offer relocation assistance to new employees. In this role, you will: Review, improve, and clean up code across training frameworks and adjacent infrastructure. Identify risky or low-quality changes before they land, and raise the code quality bar without slowing the team down. Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure. Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling. Improve the reliability, maintainability, and usability of the robotics team’s training framework. Move quickly on practical engineering problems that directly affect team velocity. You might thrive in this role if you: Have strong software engineering fundamentals and excellent code review judgment. Have experience with ML systems, training fr

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role As a Senior Software Engineer on Sentry’s AI/ML team, you’ll be responsible for building the evaluation infrastructure that measures the accuracy, reliability, and real-world performance of our AI systems. This role is critical to ensuring that our debugging agents and AI-powered features behave correctly, safely, and predictably as they scale. You’ll design datasets, benchmarks, and test harnesses that turn ambiguous AI behavior into measurable signals, helping the team ship AI with confidence. In this role you will Design and build robust evaluation frameworks to measure accuracy, reliability, regressions, and edge cases in AI systems Create and curate high-quality datasets, golden test cases, and benchmarks grounded in real production data Build automated test harnesses and metrics pipelines to continuously evaluate models, prompts, and agentic workflows Partner closely with applied AI engineers and product leaders to define what “good” looks like and translate it into measurable criteria Own the evaluation lifecycle for major AI initiatives, from early experimentation through production monitoring You’ll love this job if you Care deeply about correctness, rigor, and measurement in AI systems Enjoy turning fuzzy product goals and model behavior into concrete tests and metrics Like building foundational infrastructure that unlocks faster iteration and higher confidence for the entire AI team Thrive in cross-functional environments and enjoy influencing model design through better evaluation Qualifications Minimum 5+ years of professional experience with a Bachelor’s degree in computer science, machine learni