Partner Development Manager in San Francisco

The Datadog for Startups (DDFS) program helps the next generation of fast-scaling companies adopt best-in-class observability and security from day one. We're looking for the technical engine of this program - someone who can sit across from a startup CTO, earn credibility in the first five minutes, and help them see how Datadog fits into their stack before they've even finished describing it. You'll be the first technical member on a lean, five-person team, owning the technical motion end-to-end: discovery calls, demos, startup enablement, forward-deployed engineering projects, and representing Datadog at founder events across San Francisco. This isn't a traditional SE seat - it's part solutions architect, part technical consultant, part startup evangelist, and it requires someone adaptable, proactive, and ready to take initiative without being told what to do next. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Run discovery calls with startup CTOs and engineering leads to identify quick wins, validate technical needs, and position Datadog against alternatives like Grafana, New Relic, Sentry, and Clickhouse Deliver tailored Datadog demos and help startups get instrumented quickly - removing friction, showcasing value, and ensuring smooth technical onboarding, particularly around AI/ML observability, infrastructure scaling, and security Build automation to improve internal team workflows - EX: outreach, reporting, the application process, and website updates Represent Datadog for Startups at accelerator demo days, hackathons, conferences, founder dinners, and workshops across San Francisco Build relationships across SF's startup ecosystem - founders, VCs, accelerator partners, and technical communities - and develop thought leadership content for tech

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team OpenAI’s Forward Deployed Engineering team partners with leading semiconductor companies to deploy production-grade AI systems across the entire chip design lifecycle: design, verification, and physical design. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to translate frontier model capabilities into systems that materially improve engineering workflows and accelerate innovation. Our work turns early, high-touch deployments into repeatable solution patterns, reference architectures, and evaluation practices that scale across the semiconductor ecosystem. About the Role We are seeking a highly skilled Physical Design Engineer to join our semiconductor-focused Forward Deployed Engineering team. This is a senior IC role that will begin with a strong emphasis on physical design expertise, technical judgment, advisory leverage, and customer credibility, with the expectation that the person will grow into a broader Forward Deployed Engineering role over time. In the near term, you will serve as the team’s physical design SME across semiconductor deployments: helping FDEs, Product, and Research understand backend implementation workflows, pressure-test AI-assisted solution ideas against real physical design constraints, and raise the quality of our customer-facing technical work. You will help the broader team build fluency in implementation flows, EDA tooling, signoff methodology, and the trade-offs that shape physical design decisions in practice. Over time, we expect this role to expand beyond SME support into broader FDE ownership: partnering directly with customers, shaping deployment strategy, building and iterating production-grade AI systems, driving technical workstreams, and helping turn high-touch semiconductor deployments into repeatable solutions. This is a strong fit for someone who brings deep physical design expertise today and is excited to grow into a customer-facing, syst

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team Customer education helps customers and partners build the practical skills and confidence to use AI and OpenAI products safely and effectively. The team focuses on role- and skill-based learning paths, practical content, and product experiences that accelerate learning in the workplace. It brings together learning and enablement expertise, field insight, product signals, and measurement to improve learner and business outcomes. Together, these experiences will help enterprise users build practical AI skills, apply them with confidence in their work, and demonstrate what they can do. Employers will gain a clearer view of workforce skills and progress, helping them recognize capability, focus development where it matters most, and build confidence in workforce readiness. About the Role We’re looking for a full-stack engineer to define and build a new class of learning experiences. This is an early-stage product area where technical judgment, product sense, and learner empathy are critical. You will be setting a technical vision for how people use AI to learn how to use AI, safely and beneficially. This is a hands-on, 0-1 product engineering role with broad technical and product ownership. You’ll set direction, make foundational decisions, and ship the first versions of experiences that can grow into the default way people learn at work. You will drive full-stack product experiences end to end, from prototype through launch, instrumentation, iteration, and production hardening. The work spans interaction design, frontend implementation, backend APIs and services, learner state, content and runtime integration, telemetry, evaluation, reliability, safety, accessibility, and launch readiness. You’ll work closely with our education, GTM, and engineering teams to translate how people learn into products people want to use. bring role- and skill-based learning paths into the product, designing coaching, feedback, and adaptive support which responds to each lea

About the Team The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer feedback into rigorous insight products that help leaders and field teams understand where customers are succeeding, where adoption is blocked, and what actions will accelerate durable growth. We are building systems that make customer intelligence proactive: surfacing risk, expansion potential, product gaps, and repeatable playbooks before they show up as escalations or missed opportunities. About the Role As the Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success, you will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. You will build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor. You will also be expected to build and lead a small mighty team over time: setting direction, hiring and developing talent, creating operating cadences, and holding a high bar for technical rigor and business impact. You will lead the development of models, metrics, and decision systems that recommend what GTM and Technical Success teams should do next, explain why, and measure whether those interventions worked. Your work will help customers move from pilots to production, deepen usage across products, identify high-value use cases, reduce churn risk, and create a f

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. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction

About the Team OpenAI is building the world’s most advanced AI infrastructure ecosystem. The Site Readiness & Development team owns the upstream diligence and development work required to convert powered-land opportunities into executable infrastructure options. About the Role The Site Selection Lead sets the site-selection strategy for powered-land and greenfield/brownfield opportunities. This role defines, with cross-functional partners, what makes a site attractive, executable, and scalable, then turns that shared rubric into portfolio choices and deployment plans. Key Responsibilities Own the site-selection strategy across priority geographies, including market maps, pipeline segmentation, source refreshes, live-location tracking, and portfolio prioritization. Convene Power, Land, Development, Engineering, Construction, Environmental, Community, Commercial, Legal, and Finance partners to define the shared rubric for a high-quality site. Translate that rubric into clear screening criteria across power readiness, land control, timing, scale, cost, community risk, environmental constraints, AHJ path, budget, schedule, and counterparty credibility. Orchestrate Commercial, Legal, Finance, Power, and Development teams to shape exclusivity, initial terms, site-control strategy, funding assumptions, and the path to deployment before deeper commitment. Build a deployment plan for top candidates that identifies capacity, sequencing, capital implications, critical-path approvals, risks, owners, and stage-gate decisions. Lead conceptual site planning and test-fit screening using boundaries, map layers, buildings, substations, roads, parking, laydown, stormwater, utility corridors, acreage, and estimated load. Maintain a single decision-support view of pipeline stage, site health, power readiness, finance review, maps, project evidence, outstanding source data, owners, deadlines, and escalations. Present executive-ready advance, defer, or stop recommendations with clear

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking a highly skilled Physical Design Engineer with deep expertise in physical design and methodology. This individual contributor role sits within our physical design team and is central to delivering power, performance, and area (PPA) optimized datapath and interconnect solutions for next-generation AI accelerators. You’ll work closely with RTL designers to define and execute on physical design strategies. You will develop tools, flows and methodologies to increase team productivity. Your work will directly impact silicon’s performance and cost efficiency, as well as the team’s execution velocity and quality. In this role, you will: Develop, build and own tools, flows and methodologies for physical implementation Own physical implementation of floorplan blocks from floorplanning to final signoff Collaborate with RTL designers to drive optimal block implementation solutions Analyze and optimize design for timing, power, and area trade-offs, working in collaboration with EDA vendors and ASIC partners Qualifications: BS w/ 4+ or MS with 2+ years or PhD with 0-1 year(s) of relevant industry experience in physical design and methodology development Demonstrated success in taping out complex silicon designs Hands-on experience with block physical implementation and PPA convergence Strong coding experience with python, bazel, TCL Strong experience building physical design tools, flows and methodologies Strong understanding of microarchitecture, RTL design,

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 are seeking a Mechanical Engineer to design and prototype novel tactile, proprioceptive and force sensor solutions. You will work closely with experienced engineers and cross-functional partners to set functional requirements, develop and iterate on hardware to meet program expectations. This role is aimed at candidates with strong fundamentals in mechanical system design and robotic sensing including tactile sensors, force sensing and position sensing. You will contribute to real hardware programs moving from prototype through early production. You will lead both new sensor subsystem development and ongoing improvements to existing systems based on testing, field performance, and manufacturing feedback. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the design and iteration of mechanical subsystems, including tactile sensors, load cells, force torque sensors and joint encoders. Create and maintain CAD models, assemblies, and drawings with appropriate tolerancing and documentation. Build and test prototypes, supporting debugging of mechanical issues such as fit, alignment, friction, and wear. Assist in developing test methods and executing validation to evaluate performance, durability, calibration and failure modes. Work with cross-functional teams to integrate mechanical components with sensors, actuators, and control systems. Support transition of designs from prototype to manufacturable assemblies, incorporating DFM and DFA considerations. Collaborate with manufact

About the Team The Intelligence and Investigations team seeks to rapidly detect and disrupt abuse in AI technologies to ensure their safe use. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits all of humanity. About the Role As an Intelligence Systems Engineer, you’ll be focused on advancing our Intelligence & Investigations efforts at OpenAI, ensuring the safe and responsible use of AI across our products and services. We are seeking a self-starter to prototype, develop, and maintain new tools and processes that integrate OpenAI’s models and infrastructure to enable internal teams to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. You will be a crucial technical bridge between our data scientists and subject matter experts and technical teams like Platform Integrity, Safety Systems, and Research by leading the development of innovative tools and processes that bolster goals in scaled collections, investigations, and analysis. The ideal candidate has strong analytical and data skills, with a background in both prototyping and building scalable systems that can swiftly detect emerging threats, process vast amounts of information, and deliver insights to stakeholders. We value professionals with outstanding communication skills, a commitment to continuous learning, and who are dedicated to promoting the responsible use of AI. 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: Prototype, build, and maintain at-scale intelligence systems that detect, triage, and monitor targeted signals from both open-source and internal data Analyze requirements and deliver end-to-end solutions that address

About the Team Like every team at OpenAI, the Marketing team contributes to our broader mission of ensuring that artificial intelligence benefits all of humanity. We develop and execute strategies that build understanding of OpenAI, deepen engagement with our key audiences, and communicate why we build, how our technology is creating value, and how we approach its broader societal impact. We work closely with Global Affairs, Communications, Creative, Research, Product, and other teams to translate complex topics into clear, relevant, and compelling stories. Our work spans national campaigns and locally tailored efforts, helping people understand both the opportunities created by AI and the important issues surrounding its development and adoption. About the Role We are seeking an experienced Integrated Marketing Lead to lead policy- and reputation-focused campaigns that strengthen the OpenAI brand nationally and within local communities. This person will spearhead integrated campaigns and corporate communications initiatives that help people understand why OpenAI builds, the impact of our technology, and how we are engaging with some of the most consequential issues surrounding AI—including infrastructure and data centers, jobs and economic opportunity, and youth safety. The role combines national paid media with locally relevant marketing and engagement efforts. The ideal candidate understands policy, public affairs, and civic audiences while also being a sophisticated brand marketer who can make complex subjects accessible and meaningful to a broader public. This person will bring strategic vision, sound judgment, organizational clarity, and exceptional execution to highly visible work. They will collaborate closely with Global Affairs, Communications, Creative, Research, and external agency partners to build trust and shape understanding of OpenAI at both the national and local levels. In this role, you will: Lead policy and brand campaign strategy: Develop integ

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 Product Manufacturing Engineer to drive manufacturing strategy and execution for next-generation AI hardware within the Silicon & Systems team, with a particular focus on PCBA manufacturing, assembly, process development, and production readiness. You will work closely with design engineering, systems engineering, operations, TPMs, contract manufacturers, suppliers, and other external partners to ensure new hardware products successfully transition from concept and prototype builds through NPI and high-volume production. You’ll own critical manufacturing initiatives, identify and resolve production risks, and help establish the processes and controls required to deliver complex hardware at scale. 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: Drive manufacturing and quality initiatives to ensure product success from concept and early development through NPI, production launch, and scale. Lead manufacturing process development for next-generation AI hardware systems, partnering closely with design engineering, systems engineering, operations, TPMs, suppliers, and manufacturing partners. Own PCBA manufacturing development and production readiness, including assembly processes, process validation, manufacturing test, rework, yield improvement, and successful transition into volume production. Establish NPI manufact

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 to ship AI products. THE ROLE We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done EXAMPLE INITIATIVES Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enablin

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 to ship AI products. THE OPPORTUNITY We are looking for Senior Software Engineers to join our team. This is a specialized, high-impact role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work. RESPONSIBILITIES Benchmarking : Evaluate, run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving). DevEx Improvement : Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation. Tool Development : Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking and analysis. System Profiling : Use profilers like PyTorch Profiler, NVIDIA Nsight Systems and py-spy to collect performance profiles, identify bottlenecks, and debug the compute/networking stack. Monitoring & Observability : Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance. Continuous Integration : Auto