Performance Modeling Engineer 2 in United States

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Our Sales and Solutions teams navigate hard technical conversations spanning inference performance, GPU economics, latency budgets, deployment shape. As Baseten’s platform matures, we need a dedicated owner to translate launch velocity into field readiness. As our first Product Enablement Lead, you'll sit between Product, Marketing, and Sales GTM and own how Baseten's products, features, campaigns, and market moments like the launch of GLM-5.2 or Kimi K3 or the sudden evolution of Tokenomics as a discipline get translated into field execution. You will own how these launches land with the field, how AEs and SAs stay credible on a highly dynamic technical ecosystem, and how what the field hears from customers makes it back to Product. This is a hands-on individual contributor role. You are the bridge between product, marketing, and sales. You'll build the system and run it, which includes cross-functional program leadership, direct training and enablement of in-seat reps, and content and curriculum development for managers, sellers, and new hires. Success here will depend on your ability to build repeatable systems and rhythms and to partner across the business and with your enablement colleagues to ensure alignment and speed of execution. RESPONSIBILITIES Own launch readiness: partner with Product and Marketing on positioning, write internal launch comms, and run readiness sessions so AEs and SAs can sell new pr

About the Team The GTM Strategy & Growth team drives the growth and evolution of our B2B business across products, customer segments, and routes to market. We partner closely with Product, Sales, Success, Data Science, Finance, and Marketing to define and execute go-to-market strategies for new product launches, commercialization models, customer growth initiatives, and market expansion opportunities. Our work sits at the intersection of product strategy, growth, and operations — shaping how we bring products to market, how we measure success, and how we scale adoption across customer segments. We operate across both strategic and highly operational domains, from defining long-term growth bets and commercial strategy to building launch plans, tracking performance, and driving cross-functional execution across the business. About the Role We’re looking for a strategic, hands-on individual contributor to join our GTM Strategy & Growth team and help shape how we grow and scale our B2B business across products, customer segments, and routes to market. This is a generalist role for someone who combines strong product intuition with thoughtful GTM strategy and can flex seamlessly between strategic thinking and operational execution. You’ll translate business priorities into clear growth strategies, operating plans, and cross-functional execution. Your work may span product launches, commercialization models, customer growth initiatives, market expansion, and the systems and processes that help the business scale. You should be highly analytical, comfortable working across a range of products and business problems, and experienced navigating complex cross-functional environments. Experience with technical or API-based products is valuable, but the most important qualities are strategic range, sound judgment, and the ability to turn customer, product, and market insights into practical recommendations and action. This role is based in San Francisco office, 4-5 times

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

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. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

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. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity At New Relic, we believe in a virtuous cycle where customer success fuels improved revenue performance . Our Account Manager role is a pivotal function of an updated pod structure that sits at the intersection of Customer Success, Sales, and Product. Focused squarely on securing and growing our existing revenue base. We are a passionate, upbeat, and highly motivated group committed to exceptional customer loyalty, support, and expansion. We are seeking an Account Manager to join our team and make a positive impact in the continued success and growth of our organization. In this critical role, you will be a driver of retention, adoption, and expansion. Strong leadership ensures positive relationships and alignment across Product, Marketing, and Sales, and Support. If you are passionate about building deep, strategic customer relationships and thrive in a quota-carrying environment, let's talk! What you'll do You will utilize your skills in customer success, renewals, and sales methodologies to exceed customer expectations and deliver value across multiple key performance indicators. Drive Revenue & Retention Pod Collaboration: In partnership with the Account Team, you will function as a secondary seller within a unified pod structure. This role is essential in supporting the Account Executive (Core Seller) through seamless cross-functional alignment and collaborative deal execution. You will review areas of opportunity (whitespace

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team builds next-generation AI-native silicon and systems while working closely with software, research, and manufacturing partners to co-design hardware tightly integrated with AI models. In addition to delivering systems for OpenAI’s supercomputing infrastructure, the team develops the tools, methodologies, and strategic partnerships needed to accelerate hardware innovation. About the Role We’re seeking an experienced Hardware Strategic Sourcing Manager to own sourcing strategy and supplier partnerships for fiber and optical interconnect components across OpenAI’s next-generation AI infrastructure. Reporting to the Head of Partnerships & Strategic Sourcing, you will lead sourcing across fiber cable assemblies, internal optical harnesses, fiber shuffles, optical backplane assemblies, connectorized and standalone passive optical assemblies, fiber-array units (FAUs), fiber-to-chip and coupling interfaces, detachable connectors, optical routing, and assigned optical packaging, assembly, and test services. You will work closely with electrical engineering, optical engineering, systems engineering, mechanical and packaging engineering, quality, rack integration, data-center deployment,manufacturing, supply chain, finance, legal, and program management teams to translate demanding bandwidth, signal integrity, reliability, and scale requirements into resilient supplier partnerships and scalable commercial strategies. Your work will directly support the performance, reliability, manufacturability, and scale of the high-speed optical connectivity required for OpenAI’s next-generation AI systems. In this role, you will: Develop and execute a comprehensive sourcing strategy for fiber and optical interconnect components supporting high-bandwidth AI systems and infrastructure. Own sourcing across optical fiber cable assembli

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a Robotics Control Systems Engineer to take on a foundational role within our robotics team. You’ll help architect, implement, tune, and verify the control infrastructure that enables intelligent, reliable, and responsive robot behavior. This is a deeply hands-on role focused on real-time systems, actuation, dynamics, low-level hardware interaction, and whole-robot performance. You’ll spend significant time working directly with robots onsite: debugging behavior, tuning subsystems, running experiments, and providing feedback across mechanical, electrical, and software teams. This role is based in San Francisco, CA, and requires in-person 5 days a week. In this role, you will: Design and implement real-time control algorithms for robotic systems, including motion control, feedback loops, state estimation, actuator control, and subsystem tuning. Define the control architecture from low-level actuators and hardware interfaces through whole-robot behavior and policy. Identify and characterize actuator, hardware, and software parameters through rigorous experimentation, testing, commissioning, and verification. Work with machine learning engineers to implement reinforcement learning models. Collaborate across mechanical, electrical, and software teams to integrate control logic with sensing and actuation hardware. Help inform the mechanical and electrical design to maximize capability and flexibility. Create the control system architecture; determine the correct level of abstraction from actuators all the way up to whole-robot

About the Team OpenAI's Industrial Compute organization is building and operating the infrastructure foundation for the next generation of AI. Infrastructure Operations works across facilities, hardware, network operations, incident management, data center engineering, delivery teams, and external partners to bring capacity online safely, understand its operational state, and improve it over time. As OpenAI's data center portfolio grows across first-party and partner-delivered capacity, the organization needs clear goals, trusted data, repeatable processes, and systems that make ownership, risk, readiness, and performance visible. This role will help build the operating mechanisms that allow Infrastructure Operations to scale with rigor. About the Role We are seeking a Technical Program Manager to own the systems, data, reporting, governance, and program-management backbone for Infrastructure Operations. Reporting to the Delivery & Operations Lead, you will translate strategy into executable goals and operating cadences, turn operational needs into software and data solutions, and create the mechanisms that keep a rapidly evolving organization aligned and accountable. This role will also own the current 1P+3P delivery-tracking layer within Operations: milestones, delivery timelines, quantity forecasts, risks, decisions, and executive reporting. You will partner closely with 1P Delivery Program Management, Compute TPMs, Data Center Engineering, construction, commissioning, and operations leaders to ensure that delivery information becomes complete, usable input for readiness, handover, and ongoing operations. You will own program health and the operating system around it: the goals, data definitions, workflows, reporting, decision paths, and follow-through that help functional DRIs execute. The ideal candidate is comfortable in ambiguity, technically fluent enough to implement real systems, and relentless about converting scattered information into durable mechan

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. Our Growth Marketing team is a rapidly scaling functional area, accelerating growth by connecting out-of-product and in-product experiences into seamless journeys that acquire, retain, and re-engage users, unlocking ChatGPT’s transformative potential in users’ daily lives. We work cross-functionally with product, engineering, design, data science, finance, and marketing to unlock scalable growth levers and deliver measurable impact across diverse markets. This team thrives on rapid testing, rigorous measurement, and creative problem solving, all while keeping user value at the center of our decision-making. About the Role In this role, you will build and run the creative and advertising operations system that powers OpenAI’s paid marketing programs. You will connect Creative and Growth Marketing teams, establish clear processes for producing and launching high-quality ads, and keep the operational details behind paid campaigns organized, accurate, and scalable. You will help translate growth priorities into creative briefs and testing roadmaps, coordinate assets and approvals across internal teams and external partners, and turn performance results into clear next steps. 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: Build and manage the end-to-end paid creative operating system , including creative intake, briefing, production, asset delivery, approvals, trafficking, launch, reporting, and iteration. Serve as the day-to-da

Technical Program Manager – Applied Infrastructure About the Team The Applied team safely brings OpenAI’s technology to the world, powering products like ChatGPT, and the APIs for GPT and more. Behind these products is a complex and rapidly evolving infrastructure platform that enables scale, performance, and safety. The Applied Infrastructure TPM team partners across engineering to lead foundational programs that ensure OpenAI’s infrastructure can meet current and future demand. About the Role We’re looking for a seasoned Technical Program Manager to drive critical infrastructure programs across the Applied organization. This TPM will focus on cross-cutting initiatives such as general compute capacity planning, process transformation, cost and quota attribution and optimization, and coordination across infrastructure and product stakeholders. There will also be focus on evolving OpenAI’s infrastructure to support growth, scale and new products. This work is core to how OpenAI manages and grows its infrastructure footprint in a disciplined, scalable way. Location: San Francisco, CA (Hybrid – 3 days/week in-office) In this role, you will: Serve as the DRI for complex infrastructure programs spanning CPU planning, orchestration, and other resource management domains (e.g. networking, storage). Build and operationalize systems to capture demand signals, model future capacity needs, and align infrastructure planning across internal teams and partners external to the company. Partner closely with Infrastructure, Product and Finance teams to forecast infrastructure usage patterns and ensure supply/demand alignment. Lead cost attribution and quota enforcement programs to promote stability and ensure equitable access to resources across teams. Drive simplification and standardization of infrastructure tooling and processes across Applied and Infra organizations. Drive cross functional programs to evolve our infrastructure to support new growth and scale Work with external v

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role At GitLab, we’re looking for a Talent Brand Manager to shape how current and prospective team members understand what it means to work here. You’ll bring GitLab’s employer value proposition to life through storytelling, recruitment marketing, candidate education, and experiences that connect our external reputation to our internal culture. You’ll partner across GitLab to turn talent brand strategy into campaigns and content throughout the candidate journey. This role is a strong fit for a brand, recruitment marketing, employer brand, or content professional who can move between strategy and execution. You