Performance Modeling Engineer 2 Jobs

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

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You Will: Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Perform other duties as assigned You Have: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 10+ years of experience in data engineering or a similar role. Enterprise SaaS software solutions with high availability and scalability Solution handling large scale structured and unstructured data from varied data sources Experience in building and maintaining data platform systems such as distributed compute,

Our team is seeking to extend the internship of our current AI Research Intern for the TAO (Train, Adapt, Optimize) Multi-Modal Model Development project, recognizing their exceptional performance and strong alignment with the team’s research goals. Their innovative ideas and technical contributions have significantly enhanced our work. Given the rapidly evolving field of multi-modal AI, encompassing vision-language modeling, universal segmentation, and large-scale model training, extending this internship will provide further growth opportunities for the intern while strengthening our team’s capacity to develop scalable, high-impact AI solutions. Embark on an exciting journey with NVIDIA, a global leader in AI and accelerated computing. As an AI Research Intern focusing on multi-modal AI and vision-language model development within the TAO framework in Hanoi/HCM City, Vietnam, you will be at the forefront of advancing cutting-edge machine learning research. You’ll collaborate with a talented team of engineers and researchers dedicated to developing state-of-the-art deep learning models for tasks such as image segmentation, cross-modal understanding, and universal representation learning. This internship offers a unique opportunity to contribute to next-generation AI systems with real-world impact across industries—from autonomous vehicles to intelligent content understanding. What you'll be doing: Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks. Contribute to the design and implementation of vision-language models (VLMs) and universal segmentation systems. Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability. Collaborate with cross-functional teams to integrate your research into production-le

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,

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. 5 Work Days Per Week Relocate Near Tai Seng MRT in August 2026 Medical Benefits Provided Entitled to Yearly Bonus & Performance Bonus Role Overview The Financial Analyst (Power BI Specialist) plays a key role in strengthening the company's financial planning, reporting, and analytics capabilities. This position is responsible for delivering high‑quality financial insights through advanced data modeling, interactive dashboard development, and automation of reporting processes. Working closely with FP&A, Finance, and cross‑functional business teams, the analyst drives data‑driven decision‑making by transforming complex financial data into clear, actionable insights. The ideal candidate combines strong financial acumen with deep technical expertise in Power BI, ensuring accuracy, efficiency, and scalability across the company's reporting framework. Key Responsibilities Financial Reporting & Analysis Prepare monthly, quarterly, and annual financial reports, ensuring accuracy and timeliness. Conduct comprehensive variance analysis against budget, forecast, and prior periods. Analyze key financial metrics including revenue performance, cost drivers, gross margins, working capital, and operational KPIs. Support budgeting, forecasting, and long‑range financial planning cycles. Provide ad-hoc financial modeling, scenario analysis, and business insights to management. Power BI Development & Data Visual

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

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

About the Role OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering. What You'll Do Full-Funnel Analytics Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention. Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations. Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders. Targeting, Segmentation & Propensity Modeling Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers. Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking. Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels. Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth. Campaign Analytics & Measurement Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy. Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership. Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews. Forecasting & Planning Build high-fidelity revenue and advertiser growth models to project perfor

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Global Support & Partnerships team is a critical and unique part of helping Lyft succeed in our purpose to Serve and Connect. We support Lyft's international growth by developing integration platforms that seamlessly link global customers to an exceptional customer care experience. We go beyond simply supporting customers; we build the foundational infrastructure that turns every support interaction into a moment of genuine connection. Whether supporting our established North American community or welcoming new users worldwide, we ensure a unified, reliable, and efficient experience for riders, drivers, applicants and support agents alike. We are looking for an experienced technical leader who can support our global ambition by designing, owning, and scaling the Global Support Platform. Responsibilities: Set the technical vision and strategy for a rapidly evolving product area, making high-judgment calls on architecture and technology direction Drive the adoption of AI and machine learning solutions to optimize customer support workflows and enhance operational efficiency across the platform. Lead a team of talented engineers who ship code and tackle hard engineering problems, maintaining a high bar for technical excellence Translate high-level business goals into actionable engineering projects. Own the technical roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Drive the responsible adoption of AI development tools across engineering teams - modeling effective use, establishing best practices, and mentoring engineers to improve productivity without compromising code quality or security. Champion improvements in system, observability, performance, and tech debt reduction, extending your influence beyond your immediate team. Establish best practices f