Performance Modeling Engineer 2 in United States

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

Systems Engineer (Modeling & Simulation) (Associate or Mid-Level) Company: The Boeing Company Boeing Defense & Security (BDS) is looking for an Associate or Mid-Level Systems Engineer (Modeling & Simulation) (Level 2 or 3) to join our multi-disciplined engineering team in Albuquerque, New Mexico designing and developing advanced concepts on a DOD propriety program . This position will join a multi-disciplined team of engineers and scientists to develop and test advanced concepts for the Department of Defense. Work could include such things as image processing and analysis, radiometry, modeling and simulation, evaluation of field data to anchor models, and wherever the data may lead throughout the program. The ideal candidate will have strong MATLAB or Mathematic skills, an interest in data analysis; modeling and simulation; and some knowledge of optics and electro-optics. Position Responsibilities: Assists in developing and validating requirements for various electro-optical systems and components Uses data analysis results and output of mod/sim tools to assist in the development and validation of requirements for electro-optical systems, mechanical systems, interconnects and structures Works with engineering teams to collect and analyze data used to anchor models Performs complicated trade studies, modeling, simulation and other forms of analysis to predict component, interconnects and system performance and to optimize design around established requirements Defines and conducts critical analyses of various kinds to validate performance of designs to requirements Defines and conducts tests to validate performance of designs to requirements and anchor models to fi

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: As a Senior Machine Learning Engineer, you will be a part of Airbnb's innovative pricing guidance team. Our team is a diverse group of engineers, data scientists, and product managers who are dedicated to creating optimal pricing models for our hosts. We work closely with product engineers, designers, and other cross-functional partners to ensure our models are effective, user-friendly, and contribute to the success of our hosts. ners The Difference You Will Make: In this role, you will be responsible for developing and refining machine learning models for pricing recommendations, with a particular focus on reinforcement learning techniques. Success in this role will be measured by the accuracy and effectiveness of these models, and their impact on host success rates. You will also be involved in project planning and prioritization, ensuring that our team's efforts align with Airbnb's broader strategic goals. A Typical Day: Collaborating with data scientists and product managers to understand project requirements and desired outcomes Developing, testing, and refining machine learning models, particularly reinforcement learning models, for pricing recommendations Analyzing model performance and making necessary adjustments Presenting findings and progress updates to team members and stakeholders Working with product engineers and designers to integrate models into user-friendly tools for hosts Your Expertise: 5+ years of experience in machine learning engineering Proven experience in developing and implementing machine learning models, preferably reinforcement learning mo

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 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 The Security Team is responsible for securing all things Sentry: our customers, our code, and everything in between. We are a small but growing team with broad scope, high trust, and the autonomy to tackle hard security problems with creativity and an engineering mindset. We work at a company with a strong developer culture, building a product that millions of developers genuinely love and rely on. That context shapes everything about how we operate. As a Security Engineer on this team, you'll work across application and platform security domains. You'll contribute to the practices that keep Sentry secure as we grow: security reviews, threat modeling, vulnerability management, and embedding secure coding practices into an engineering organization that cares about doing things right. You'll partner closely with product and engineering teams to influence how features are designed and built from the start. You will work as a technical collaborator who helps make the secure path the obvious one. As Sentry expands our agentic product capabilities and development practices, you'll also find yourself at the frontier of a new set of security challenges. In this role, you will Support and help mature Sentry's security review program. From secure code review, to architecture review, and threat modeling. You'll help build the processes, tooling, and culture which make security a natural part of how we ship and operate. Contribute to mature vulnerability management practices. Intake, triage, prioritization, remediation tracking, and support of our bug bounty and responsible disclosure program. Advocate for secure-by-desig

Interactive Design Engineer - HPIQ Description - About The Role As a Product Design Engineer at HP IQ, you’ll work at the intersection of creativity, engineering, and design to develop groundbreaking devices that redefine how people interact with technology. You’ll collaborate closely with industrial designers, hardware engineers, and interaction designers to transform ideas into functional prototypes and production-ready designs. From 3D CAD modeling and hands-on prototyping to engineering analysis and design validation, you’ll help solve complex mechanical challenges and drive designs from early concepts toward production. You’ll have the opportunity to take ownership of meaningful engineering work while learning from an experienced, multidisciplinary team and contributing to products that push the boundaries of what’s possible. What You Might Do Design mechanical parts, components, and assemblies for new consumer devices using 3D CAD (NX) Create detailed 2D engineering drawings, define specifications and tolerances, and work closely with overseas vendor partners to ensure accuracy and quality Design and run experiments, applying engineering analysis and test results to guide design decisions Evaluate materials, manufacturing processes, and design tradeoffs to develop robust and scalable solutions Work cross-functionally with hardware, software, industrial design, and other engineering teams to bring concepts from ideation through development Conceptualize, design, and build prototypes that quickly validate ideas Participate in design reviews, clearly communicating design decisions, technical analysis, and tradeoffs to both technical and non-technical audiences Build, test, troubleshoot, and iterate prototypes to identify issues and improve product performance, reliability, a

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Join NVIDIA's GPU Performance Infrastructure team and be part of a brand-new journey in validating and shipping next-generation GPU architectures. At NVIDIA, we empower our engineers to innovate and drive powerful performance through innovative infrastructure and workflows. This role is uniquely positioned to influence the entire lifecycle of GPU performance verification, from early-stage modelling to post-silicon validation. With our bold standards and extraordinary team, you'll have the chance to define a significant impact on the future of computing! What you'll be doing: Build and develop end-to-end performance verification infrastructure. Build scalable data pipelines to surface performance metrics from simulation, emulation, and silicon environments. Coordinate with GPU architects to craft infrastructure for performance verification of upcoming architectures. Work closely with HW teams to automate and accelerate verification workflows, enabling faster GPU build iteration. Empower GPU architects by providing insights to understand current performance and model industry-leading performance for future builds. Improve the daily workflows of the wo

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? At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology. Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI. July 31st 2025 - Cohere's Multimodal team Introduced Command A Vision: Multimodal AI Built for Business. At release our new flagship vision-language model: ● Consistently outperforms major models like Llama 4 Maverick, Mistral Medium/Pixtral Large, and GPT4.1 ● 83.1% average benchmark (73.5% MathVista, 90.9% ChartQA...) ● Built for the real world - 112B parameters running on just 2 GPUs ● Open weights live on HuggingFace With a focused team, breakthrough performance doesn't require breakthrough compute. Focus on the things that matter, and join the team. As a Member of Technical Staff with a focus on Multimodal AI, you will: Design and develop cutting-edge multimodal AI systems, integrating various modalities such as text,

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Senior Data Scientist - Network Value (Credit) The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Data Scientist supporting Credit, a critical product area within Plaid’s Network Value portfolio. You’ll become a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders, helping shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and KPIs tied to business goals and user experiences, a

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

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 building next-generation processors and systems, bringing together world-class expertise across silicon, systems, and software. We are looking for a CPU Performance Modeling Architect to help evaluate, shape, and optimize the performance of future CPU architectures. In this role, you’ll use performance modeling, workload analysis, and deep understanding of CPU architecture to answer complex questions about how a processor should be designed. You’ll work closely with CPU architects, RTL designers, software and compiler teams, and system engineers to identify performance opportunities, evaluate architectural tradeoffs, and turn modeling insights into actionable design decisions. 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 A CPU architect, performance architect, or performance modeling engineer with experience influencing CPU architecture or microarchitecture decisions. You have a strong understanding of modern processor architecture and enjoy digging into why a CPU performs the way it does. You are comfortable combining hardware architecture, software, data, and

About the Team OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads. We work closely with hardware, modeling, and architecture teams to ensure that new platforms deliver real-world performance aligned with workload needs. Our team focuses on understanding workload behavior across evolving hardware platforms—bridging the gap between theoretical capability and observed system performance. About the Role We are seeking a Workload Porting & Performance Engineer to evaluate new hardware platforms by porting benchmarks and real-world workloads, analyzing performance, and identifying system bottlenecks. In this role, you will bring up workloads on new systems, characterize performance behavior, and adapt workloads to better utilize hardware capabilities. You will play a critical role in validating new platforms and ensuring that performance aligns with expectations across compute, memory, and networking subsystems. This role requires strong hands-on experience with performance analysis, workload optimization, and system-level debugging across hardware and software boundaries. 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 Port and enable benchmarks and real-world workloads on new hardware platforms. Evaluate system performance across compute, memory, storage, and networking subsystems. Identify and analyze performance bottlenecks and inefficiencies. Adapt and optimize workloads to better utilize hardware capabilities. Develop and run performance experiments and profiling workflows. Compare expected vs. observed performance and provide feedback to: hardware architecture teams performance modeling teams system and software engineers. Debug issues across the stack, including software, runtime, and hardware interactions. Provide actionable insights to guide platform readiness and deployment decisions. Qualifications E

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 On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. Contribute to runtime improvements, compute/communication over

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’re looking for a software engineer to help build the design methodology, software abstractions, and infrastructure that enable a small silicon team to develop complex chips rapidly and with high confidence. You will turn evolving architecture and design needs into reusable tools and workflows that improve iteration speed, quality, and then apply those tools to help construct world-class silicon. You’ll work closely across architecture, design, verification, performance modeling, and systems software. This role is well suited for an engineer who enjoys building high quality software and is motivated by the challenge of improving velocity and quality of the silicon development process. In this role, you will: Develop and scale design methodologies for rapid first-party chip development and apply them to construct complex custom chips Create abstractions that allow hardware structures, configurations, experiments, and results to be represented consistently across tools. Automate high-value engineering workflows and improve their reproducibility, observability, testability, and ease of use. Partner with architects, RTL designers, verification engineers, compiler engineers, and systems software engineers to gather requirements and then implement solutions. Use methodology and tooling to identify design risks early, accelerate iteration, and improve confidence in performance and implementation tradeoffs. Contribute across multiple aspects of software and hardware

NVIDIA Architecture Modeling group is looking for Architects, Functional Modeling Engineers, and Simulation experts to join various architecture efforts across GPU/ SOC Architecture teams. A key part of NVIDIA's strength is to innovate in parallel computing fields, delivering the highest performance in the world for high-performance computing. We are constantly looking for ways to improve our SoC and Systems architecture and maintain our leadership. In this position, you will be working with other world-class architects on modeling, analysis and validation of chip & system architectures and features that advance the state of art in performance and efficiency. What you'll be doing: Modeling and analysis of SoC & Systems algorithms and features, across datacenter, automotive, and client products Build and deliver platforms for SOC's that enable left shift for the SW teams aligned with project milestones Work closely with the SOC architects and guide modeling teams to deliver high-quality functional models that involve SOC+GPU use cases Collaborate with our EDA partners to align on customer-facing technologies Develop tests, test plans, and testing infrastructure for new architectures/features and code coverage analysis and reporting Ensure alignment between the various modeling teams at NVIDIA, GPU modeling teams, and modeling teams overseas What we need to see: Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related relevant field (or equivalent experience) with 5+ years of relevant work experience. Strong programming ability: C++, C along with a good understanding of build systems (CMAKE, make) , toolchains (GCC, MSVC) and libraries (STL, BOOST) Computer Architecture background with experience in modelling wit