Performance Engineer, Inference Systems

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for talented systems developers and researchers to join the Snowflake AI Research team and advance the state of the art in LLM inference systems and optimization . Our mission is to build the next generation of high-performance and intelligent inference systems . We optimize not only how fast and efficiently models run, but also how quickly inference systems can adapt to new models, architectures, hardware, and workloads. Our work spans the full inference stack—from distributed serving and runtime systems to GPU kernels and model-system co-design. We explore techniques such as adaptive parallelism, speculative and parallel decoding, disaggregated inference, scheduling and batching, KV-cache optimization, model swapping, quantization, and GPU kernel optimization to push the frontier of latency, throughput, scalability, and cost. Beyond optimizing individual models, we are building intelligent and adaptive inference systems that can automate performance optimization—rapidly profiling new models and workloads, identifying bottlenecks, selecting effective execution strategies, and adapting system configurations with minimal manual tuning. We embrace AI-native engineering , using AI not only as the workload we optimize, but also as a tool to accelerate system deve

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron's Data Center Workload Engineering team tests how memory and storage products perform in complete data center systems. We deploy customer-representative AI, database, virtualization, and software-defined storage workloads in production-class labs. We trace I/O from the application through the system to the SSD to explain performance and identify opportunities to improve it. As a Principal Systems Performance Engineer, you will lead complex performance studies from the initial question through the final recommendation. You will personally lead the hardest investigations while setting technical direction for the team. Your work will guide SSD architecture and product development and help customers get the best performance from Micron products. This is a hands-on senior individual-contributor role. Key Responsibilities Lead application performance studies on enterprise servers, GPU-accelerated systems, and data center storage platforms. Deploy customer-representative workloads across one or more areas, such as AI training and inference, checkpointing, KV-cache offload, data preparation, databases, virtualization, and software-defined and object storage. Develop test plans with clear hypotheses, realistic configurations, appropriate controls, and repeatable methods. Instrument systems and trace I/O from the application through the software and storage stack to the SSD. Measure application throughput

About the Job Set the performance direction behind large-scale AI systems built for real deployment. As a Principal AI Performance Engineer, you will define how Graphcore analyzes and optimizes AI training and inference workloads. Your work will shape decisions across hardware, software, networking and system architecture. You will lead the hardest performance investigations, from model behavior to multi-node scaling. You will turn profiling, benchmarking and modeling evidence into technical roadmaps and engineering priorities. You will set measurement standards, guide distributed communication strategy and review critical C++ and Python tools. Your judgment will help teams make better decisions when data is incomplete. This role gives you rare influence across AI infrastructure at data center scale. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work happens through evidence, technical ownership and direct cross-team influence. You will guide strategy, resolve complex tradeoffs and raise performance-engineering standards across the organization. Decisions are shaped by benchmarks, simulations, models and clear technical debate. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Deep experience profiling and optimizing AI, machine learning or high-performance computing workloads at scale. · Proven technical leadership across complex performance-engineering or system-architecture initiatives. · Expert C++ and Python skills, including reliable tools or performance-sensitive software. · Expert understanding of compute, memory, communication and scaling behavior in distributed systems. · Ability to define benchmarks, measurement practices or optimization sta

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 ship AI products. THE ROLE We're looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users. EXAMPLE INITIATIVES You'll get to work on these types of projects on our Inference Platform: The Baseten Inference Stack at NVIDIA Dynamo Day 2x faster inference with KV cache-aware routing How Baseten multi-cloud capacity management (MCM) unifies deployments RESPONSIBILITIES Build the infrastructure and orchestration systems that de

About the Job Turn complex AI workload signals into faster, more efficient systems at data center scale. As a Senior AI Performance Engineer, you will analyze and optimize AI training and inference workloads across large-scale distributed systems. Your work will connect compute, memory, communication and software behavior. You will own complex performance investigations from problem definition through validation. You will turn profiling, benchmarking and modeling results into improvements engineers can build from. You will design benchmarks, investigate system bottlenecks and optimize distributed communication software across technologies such as MPI, NCCL, UCX and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale deployment. This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to own complex technical work and coo

About the Job Lead performance work that turns large-scale AI workloads into faster, more efficient systems. As a Staff AI Performance Engineer, you will analyze and optimize AI training and inference workloads across distributed systems. Your work will connect compute, memory, networking and software behavior. You will lead complex performance workstreams across hardware and software. You will find bottlenecks, validate improvements and turn performance evidence into practical engineering decisions. You will build benchmarks, profile demanding workloads and develop C++ and Python tools for analysis and optimization. Your recommendations will help teams improve efficiency, scalability and reliability. This role gives you broad technical scope across AI infrastructure at data center scale. It is based in Milpitas, California. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will lead investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to lead technically complex work and coordinate improvements across teams. · Familiarity with MLPerf, a