Performance Engineer

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role Mach Industries is searching for an experienced Cycle Analyst/Designer to guide the engine cycle model towards further maturity, validate test data and develop new engine cycles from a clean sheet. The analyst will own the cycle deck and be responsible for guidance on engine capability and improvement. They will work daily with aerodynamic, structural and mechanical designers to improve upon current designs and guide the future of the engine(s). We are on a mission to deliver high-performance small turbine engines at scale needed by rethinking the fundamentals to enable high-rate, scalable manufacturing. This is an opportunity to shape the future of propulsion from the ground up, and it takes the best people to make that happen. We are looking for those who thrive in diverse, fast-paced, high-expectation environments and are driven to build what’s never been built before. Key Responsibilities Improve cycle model in NPSS and develop cycle models from scratch. Create analytical tools to perform basic analysis. Develop tools/workflows for speeding up repetitive tasks. Work with aerodynamic, structural and mechanical engineers to develop the ultimate components. Develop test procedures for determining performance of components. Analyze test data wit

The Performance Research Engineer will play a critical role in advancing TaylorMade's leadership in golf equipment performance. This role bridges physical testing, player testing, Tour-level data collection, and advanced analytics to deliver actionable insights that influence product design, product validation, and performance optimization. The ideal candidate is a hands-on engineer with strong mechanical aptitude, advanced data skills, deep golf intuition, and the ability to translate player feedback into clear engineering direction. Essential Functions and Key Responsibilities: Lead the design and execution of advanced performance testing protocols for golf clubs and balls, including lab, player, field, and Tour-based testing environments. Serve as a category-focused Performance Engineering owner for one or more product areas, with potential emphasis across Woods, Irons, Putter/Wedge, or cross-category initiatives. Support PGA/LPGA Tour and elite-athlete testing by collecting clean, repeatable, decision-ready data while operating professionally and respectfully in player-facing environments. Analyze large datasets from lab, player, and field testing to extract insights on ball speed, launch, spin, consistency, delivery, impact location, dispersion, and performance tradeoffs. Translate Tour and player-test observations into clear engineering recommendations, product questions, validation plans, and follow-up experiments. Develop and maintain automated data pipelines, dashboards, and reporting tools for performance tracking, project communication, and cross-functional decision-making. Collaborate with R&D, Product Development, Tour, Fitting, Consumer Insights, and Analytics teams to integrate player feedback and real-world data into product design.

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity As a Graduate Performance Engineer, you will contribute to the design, integration, bring-up, and validation of complex server- and rack-level performance of elaborate, large-scale systems. You will work alongside experienced engineers, software developer, and cross-functional partners while building practical skills in component, system and scale up/out performance optimization and design. Start: September, 2027 Location: Austin, Texas, USA What You’ll Do Support the design, peer review, bring-up, and debug of complex server- and rack-level systems. Assist with modeling, design and evaluation of the complete software and hardware stack identifying performance bottlenecks, possible solutions and testing those outcomes. Collaborate with many different teams across both hardware and software development and testing. What You’ll Bring A bachelor’s or master’s degree in electrical engineering, computer engineering, or a related discipline, completed before the role’s start date. Equivalent relevant education or practical experience will also be considered. Foundational knowledge of software development, hardware architecture and general understanding of performance implications. Hands-on experience gained through coursework, laboratories, internships, research, student projects, or personal projects. Ability to analyze technical problems, document your work, communicate clearly, and collaborate effectively. Curiosity, sound engineering judgment, a

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 inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference. EXAMPLE INITIATIVES You'll get to work on these types of projects as an Inference Performance engineer: Agentic Kernels in Production How we built the new fastest API for GLM-5.2 Live draft model training for speculative decoding Making Kimi K3 Tokenization 18x faster The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms. Profile and optimize inference end to end, from

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 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