Performance Fitter Jobs

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. 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 o

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 We are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. Improve AI-assisted optimization systems for sp

To support the FP&A function in delivering accurate and timely budgeting, forecasting, MIS reporting, financial analysis, and business performance insights. The role will assist in data consolidation, variance analysis, management reporting, and stakeholder coordination, while developing core financial planning and analytical capabilities to strengthen the organization's decision-making process and build a sustainable talent pipeline for future FP&A leadership requirements. Source: Adani Group | Job ID: 58554

About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja , the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company’s products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we’re building an AI-native culture. We’re not waiting for the future; we’re creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what’s possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn’t been invented yet, you’ll fit right in. We are open to candidates in the Montreal or Mississauga area. Spécialiste, Médias sociaux payants – Marketing de performance DTC À propos de nous SharkNinja est une entreprise mondiale de conception de produits et de technologie, dotée d’un portefeuille diversifié de solutions de style de vie cotées 5 étoiles qui améliorent le quotidien des consommateurs partout dans le monde. Grâce à ses deux marques mondiales de confiance, Shark et Ninja , l’entreprise possède un historique éprouvé d’innovation disruptive et de lancement continu de produits grand public qui lui ont permis d’élargir sa présence dans de

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a CPU Verification Fellow to lead verification strategy and execution for next-generation RISC-V high-performance processors. This role requires deep CPU verification expertise, strong microarchitecture understanding, and the ability to guide large engineering teams from early design through tapeout and post-silicon validation. The ideal candidate has verified complex out-of-order, speculative, superscalar CPUs and can define scalable methodology across simulation, formal verification, emulation, FPGA, and silicon bring-up. This role is hybrid, based out of Santa Clara, CA or Austin, TX. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You have deep experience verifying high-performance superscalar CPUs, ideally including out-of-order and speculative processors. You have strong knowledge of RISC-V architecture, including ISA compliance, privileged architecture, virtual memory, atomics, vector extensions, and memory model behavior. You are highly proficient in SystemVerilog, UVM, constrained-random verification, assertions, functional coverage, and advanced debug methodologies. You have hands-on experience with CPU refere

Senior Analyst, FP&A - Commercial Network Performance — Work At Home-California. Apply via Workday.

Analyst, FP&A – Medicare/Medicaid COGS & Network Performance — CT - Hartford. Apply via Workday.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization. The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. As a Member of Technical Staff, you will: Design and write high-performant and scalable software for training. Understand a

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. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Our diverse team of technologists have developed a high performance RISC-V-based CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a talented engineer to build and run the performance infrastructure shared by our RISC-V Software and RISC-V Performance teams. This is the plumbing that both teams' performance work stands on — benchmarking automation, data collection, and workload capture across silicon, FPGA/emulation platforms and performance models. You'll work across both teams, enabling performance and software engineers to spend their time on analysis and optimization instead of running experiments by hand. This role is hybrid, based out of Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Great at identifying problems and developing solutions, with a bias toward owning the systems you build. Enjoys building tools and optimizing workflows so other engineers can move faster. Strong Linux systems engineer, c

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a talented engineer to join our CPU design team to drive infrastructure for performance analysis, correlation and verification. You’ll work on a CPU based on RISC-V ISA, collaborating with core architects and RTL teams to deliver a highly efficient and performant design. This role is hybrid, based out of Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong problem solver who can identify complex issues, develop practical solutions, and drive them through implementation. Enjoy building tools and improving the infrastructure, workflows, and methodologies that make CPU development more efficient. Skilled in C++ and Python, with experience using industry-standard compilation, simulation, and emulation tools. Experience with verification infrastructure and methodologies along with knowledge of high-performance CPU architecture and microarchitecture. Proficient in debugging RTL and logic across multiple design hierarchies and pre-silicon environments. What We Need Join a team driving improvements in CPU microarchitecture, verifying performance, and correlating results between RTL and the performance mode

Managing Consultant, Advisors & Consulting Services, Performance Analytics — Mexico City, Mexico. Apply via Workday.

Senior Analyst, FP&A - Large Client Revenue, COGS & Network Performance — 2 Locations. Apply via Workday.

Hiring for IFM role - Compliance Executive, Finance Executive/Manager, Performance Manager/Executive, Sustainability Manager, AFM(Soft/Tech), FM (Soft/Tech), MIS Coordinator — 2 Locations. Apply via Workday.