Performance Fitter in United States

About the Team The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. About the Role As a Performance & Systems Engineer on the Codex team, you will be responsible for whole-system optimization across a complex, evolving stack. Codex spans LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. Your job will be to identify and land high-leverage changes—across infrastructure, modeling, and product layers—that make Codex agents significantly faster and cheaper to serve. We’re looking for generalists who thrive in ambiguity and love chasing performance bottlenecks to ground. This is a high-ownership role where your work will directly improve the experience of millions of users. 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: Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond. Build tooling to measure, profile, and optimize system performance at scale. Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost. You might thrive in this role if you: Have experience operating across both ML systems and cloud infrastructure. Enjoy diving into messy, ambiguous problems and emerging with clear wins. Think holistically about performance, balancing spee

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1–2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. 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. Key Responsibilities Support the development and maintenance of performance modeling tools and frameworks Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems Help analyze distributed system scaling behavior and identify performance bottlenecks Run simulations and analytical models to support architecture and infrastructure decisions Partner with senior engineers to evaluate design tradeoffs across hardware and system components Interpret modeling outputs and help translate findings into clear recommendations Vali

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and inform next-generation infrastructure design. About the Role We are seeking Performance Modeling Engineers to develop and apply modeling tools that evaluate AI system performance and inform architectural decisions. In this role, you will work closely with the Performance Modeling Lead and partner teams to analyze system behavior, run simulations or analytical models, and help quantify tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks and applying them to real-world questions that impact system design and vendor decisions. This role is well-suited for engineers with strong software or modeling backgrounds who are interested in developing deeper expertise in system architecture and AI infrastructure. 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. Key Responsibilities Develop and maintain performance modeling tools and frameworks. Build models to evaluate system behavior across: compute, memory, and interconnect subsystems distributed system scaling and bottlenecks. Run simulations and analytical models to support architectural tradeoff analysis. Collaborate with performance modeling lead and system architects to answer forward-looking design questions. Analyze and interpret modeling outputs, translating results into actionable insights. Validate models against real system measurements and workload behavior. Contribute to improving modeling fidelity, usability, and scalability. Qualifications Strong software engineeri

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. 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. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte

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.

NVIDIA’s Silicon Co-Design Group sits at the crossroads of architecture, silicon, systems, and manufacturing, where first-principles thinking and engineering judgment at the highest level translate directly into product outcomes at scale. We are looking for a Principal Performance and Manufacturing Architect who has built the models, defined the specs, and seen them validated through silicon. You have owned the connection between design intent and manufacturing reality, not as a reviewer or a contributor, but as the person who set the methodology and proved it worked. You turn ambiguous physical phenomena into quantified, defensible margin terms. You do not wait for data to confirm your hypothesis; you design the experiment that gets it. You improve how the organization ships products after every program. The exceptional hire also uses AI deliberately — with proven workflow impact and the judgment to know where it compresses real work and where it introduces risk. What you'll be doing: Own the physics, from mechanism to margin. Build first-principles models connecting AVF, defect mechanisms, and DVFS transients to field FIT, system-level yield, and DPPM vs. coverage — calibrated per node and population shift — so every margin term in the V/F curve and P-state table is named, sourced, and defensible. Set the screen that resolves escapes. Specify ATE and SLT voltage, frequency, and timing conditions that capture worst-case transient VF windows — making it unambiguous whether a marginal defect or timing violation is detected or escapes at every manufacturing stage. Make the POR the authoritative source. Author the methodology document for each program and drive alignment across build, product definition, reliability, and test engineering — so every team is making decisions from the same model. Prove the model before produc

High Performance Workstation Business Development Manager- AMD Description - Sales and Technical Consultant, High-Performance Workstation Segment We are seeking a customer-facing AI and Acquisition subject matter expert role on the HPI Advanced Compute Solutions (ACS) sales team and will focus on growing HP’s Z high-performance workstation Total Addressable Market (TAM) within the AI PC market. This individual will be responsible for working with customers and partners in support of attracting new customers and growth in HP’s high performance compute solutions . The role analyzes market competition, gathers customer feedback, and shares insights with internal teams for improvement. The ideal candidate will possess a breadth of abilities and skills, including client hardware knowledge, AI and machine learning applications and solutions, strong marketing and presentation skills, solid understanding of customers’ business and decision makers, and strong team leadership to drive growth with an emphasis on Advanced Micro Devices (AMD) platforms with customers and partners. Most importantly, the role offers the opportunity to be a business leader in support of the sales teams nationally - contributing to the strategy, setting direction, and achieving success in AMD and HP. The role requires someone to be self-driven, capable of operating autonomously through ambiguity, and constantly striving for excellence. THE PERSON: We seek an individual with exceptional technical & business knowledge and familiarity with AI trends in the PC market. This individual should be comfortable working: Dynamic environment and have experience with PC client and AI hardware, software and systems. Work independently within a core team is important, and you will rely upon your excellent communication and relat

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. Measure, re

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Your Role at Baxter THIS IS WHERE you build trust to achieve results As a Field Sales Performance Manager, you take pride in representing our Advanced Surgery division at Baxter. Your keen understanding of our deep portfolio of surgical products and belief in the value and quality they provide to patients fuels your confidence. Our sales reps and customers trust you and appreciate your knowledge and curiosity when finding solutions to meet their needs. You enjoy being on location, building relationships, and establishing trust with the doctors and nurses who use Baxter solutions every day. Being one of our Advanced Surgery Field Sales Performance Managers, you'll play an integral role in developing our sales talent and elevating clinical and commercial capability across the organization. This is a leadership role that sits on each area leadership team: the successful candidate earns influence by coaching, mentoring, and building a culture of continuous learning & performance across the field. Partnering closely with the Area Vice President

Job Details: Job Description: Intel is shaping the future of technology to help create a better future for the entire world. Our work in pushing forward fields like AI, analytics, and cloud-to-edge technology is at the heart of countless innovations. With a career at Intel, you'll have the opportunity to use technology to power major breakthroughs and create enhancements that improve our everyday quality of life. Join us and help make the future more wonderful for everyone. Want to learn more? Visit our YouTube Channel or the link below. Life at Intel The Role and Impact As a SoC Power Thermal Performance Validation and Optimization Engineer, you will play an essential role in ensuring Intel's products achieve optimal power, thermal, and performance benchmarks at the system-on-chip (SoC) level. In this position, you will develop and execute validation methodologies, optimize hardware/software solutions, and perform SoC-level debugging to address power, thermal, and performance challenges. Your contribution will directly impact Intel's ability to deliver competitive, high-performing products to market. Business Group This role is part of Intel's Data Center Group (DCG), which focuses on designing innovative solutions to power the next generation of computing platforms for data centers. As a member of the PTP PreSi Correlation Solution team, you will contribute to shaping the development and validation processes for cutting-edge technologies, ensuring Intel meets and exceeds industry standards for performance and efficiency. Key Responsibilities: Develop and execute SoC-level power, thermal, and performance validation and

NVIDIA's Silicon Co-design Group (SCG) sits at a rare intersection: we own the full product development lifecycle, from early architecture definition through silicon bringup to product release. Our ArchDev team is the hub for silicon and system-level feature development, driving tradeoff analysis, system integration, and POR alignment across the entire organization. If you want to see your work go from whiteboard to world-class silicon, this is where that happens. What You'll Be Doing: Architect and integrate system-level performance and power management features, controllers, and policies to optimize product efficiency across datacenter and client products . Build feature roadmaps to address low-power, low-noise, and performance-per-watt product needs through prototyping, use-case analysis, and cost/benefit trade-offs. Partner with architecture, ASIC, board/platform, software/firmware, and marketing teams to drive design decisions and debug complex issues. Track industry trends and market needs and translate them into forward-looking roadmaps that keep NVIDIA's products ahead of the curve. Lead debug efforts, develop workarounds, and support bringup , validation, manufacturing, and customer escalations. What We Need to See: <

Job Details: Job Description: As a Senior Power and Performance (PnP) Engineer, you will be responsible for PnP product execution focused on measurements, analysis, and projections/estimates of Intel's unlaunched notebook and desktop products. Based on your technical knowledge of both Intel and the competition, you will help influence OEM customers, internal marketing teams, internal engineering teams, debug Intel silicon/platform on PnP issues, and be an integral part for Intel product launches. Core responsibilities to include following: Measure, analyze, and debug workloads to call out any power and/or performance gaps and close with internal engineering teams/architects Measure and analyze SoC/CPU and platform power on a rail by rail basis and debug any issues/gaps Align with other internal engineering teams and architects to ensure there is consensus on power and performance projections/estimates/measurements for both internal and external communication Guide, educate, and influence internal engineering teams, field account teams, and marketing teams on power and performance positioning of Intel products Create power and performance estimates on upcoming Intel products based on workloads to aid marketing decisions and help set internal KPI targets Own the publication of the Power Performance Guide (PPG) collateral to help guide OEM customers Bring up full test platform to enable both power and performance measurements including setup, calibration, and measurements. Qualifications: You mus

Power and Performance Validation Engineer About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debug compl