Jobs in United States

Production Tech in United States

1,384 active opportunities · Updated October 2026

Explore current production tech jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 New York, new york, United States· Full-time
✓ High-confidence listingCompany trend -67.9%
Quick readStrong listing-quality and freshness signals

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Talent at Modal Modal is growing fast, and the programs that bring people in and set them up to succeed are still being built. You'll join the Talent team as one of its first hires focused purely on programs; working closely with recruiting and leadership to build the events, internship, and campus presence that shape how the best people discover and experience Modal for the first time. The Role As Talent Programs Manager, you will own Modal's talent events, our intern program, and our presence at career fairs, end-to-end. This is a build-from-the-ground-up role for someone who wants full ownership rather than an existing playbook to execute. You'll work directly with recruiters, hiring managers, and marketing to make sure every program ladders up to real hiring outcomes, and you'll be the person who makes candidates' and interns' first experience of Modal a great one.

AIGoExcelMarketing
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📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -83.9%
Quick readStrong listing-quality and freshness signals

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,

PythonAWSRestAI
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📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -87.2%

From $110K/yr

Quick readStrong listing-quality and freshness signals

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

Machine LearningAIGoRust
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -73.5%
Quick readStrong listing-quality and freshness signals

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

PythonSQLAWSGit
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📍 New York, New York, United States· Full-time· Remote
✓ High-confidence listingCompany trend -73.5%
Quick readStrong listing-quality and freshness signals

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. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

PythonAWSGitMachine Learning
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📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -87.2%

From $156K/yr

Quick readStrong listing-quality and freshness signals

As a Product Manager – IaC Detection, you will define, build, and launch capabilities that proactively detect infrastructure issues in code (e.g. Terraform, Helm) before they can be deployed into production and escalate into production incidents. The Infrastructure Monitoring team has pioneered shift-left detection in the industry with Bits Infrastructure Operations , and we’re looking for a Product Manager to expand this capability to a broader set of use cases Customers (and thus developers) are increasingly standardizing on IaC tools to deploy and maintain ever-growing infrastructure in the cloud. At the same time, SREs and Infra teams struggle with an increasing number of production incidents. By shifting-left and identifying high-impact infra changes before they are deployed, we help reduce production incidents, reduce waste, and free up SRE time to focus on value-added tasks. You will own the roadmap to expand IaC detection to a broader set of use cases, including cost detection, blast radius impact, as well as configuration changes on infrastructure powering applications like nginx, postgres and more. You’ll partner closely with Engineering, Design, and customers to build and iterate on the roadmap, build product market fit, drive customer adoption (including internal usage), and focus on coverage and correctness of the AI system. This is an opportunity to lead an initiative at the intersection of AI, infrastructure operations, and autonomous observability. 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: Lead the product roadmap for IaC Detection, enabling customers to proactively detect and catch high-impact infrastructure and configuration changes before they are deployed into production and escalate into incidents. Define the end-to

GitAIRustTerraform
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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. ABOUT THE ROLE This role owns Baseten's relationships and market intelligence across the hardware and chip layer of the compute stack: NVIDIA directly and key OEM partners such as Dell, Lenovo, Pegatron, and Supermicro. As Baseten's compute strategy increasingly depends on hardware access and terms, this role is central to keeping Baseten ahead of the market. WHAT YOU'LL DO Build and maintain relationships across NVIDIA and key OEM partners (e.g. Dell, Supermicro) Track market intelligence on hardware availability, roadmaps, and terms to keep Baseten informed and strategically well-positioned Support deal structuring and negotiation in partnership with Baseten's deal-making function Work closely with Infrastructure and Hardware Platform engineering teams to ensure consistent, high-quality provider relationships and engineering partnerships Represent Baseten credibly across senior relationships in the hardware ecosystem, escalating to company leadership when strategically valuable WHAT WE'RE LOOKING FOR Existing relationships and credibility within the NVIDIA, OEM, and HPC ecosystem Strong relationship-management instincts, with the judgment to know when to bring in senior leadership for maximum impact Comfort operating in a fast-moving, high-stakes market where hardware access can be a major competitive differentiator Collaborative style — this role depends on close coordination with engineering counterparts, not just ex

Machine LearningAIGoHR
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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. ABOUT THE TEAM Supply is responsible for knowing everything happening in the compute market: who's building, who's buying, and on what terms. This role owns a specific and fast-moving slice of that map — emerging clouds and international markets — and owns the full relationship lifecycle in that space, from first outreach through to closed terms. RESPONSIBILITIES Build and maintain a real-time picture of the emerging cloud and international compute landscape — who's active, what they're building, and what terms are available Own the full partnership lifecycle in this space — from identifying and sourcing new providers, to negotiating terms, to ongoing relationship management Develop and manage relationships across a broad set of emerging and international providers, from account reps up through leadership Identify, structure, and help close opportunities where Baseten can move quickly to secure favorable capacity terms Define compelling value propositions tailored to different types of providers, rather than a one-size-fits-all pitch Partner closely with others in the team already covering this space to build out a durable, well-organized intelligence and relationship function Collaborate with the broader Supply and Deals functions to bring opportunities to the table and support negotiation when it's time to close WHAT WE’RE LOOKING FOR Equal parts relationship-builder and operator — you can open a door and also drive it

Machine LearningAIGoHR
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 This is a sourcing-first role, not a deal-closing role. Baseten needs someone who can build and maintain deep relationships across the long tail of data center and powered land providers, well beyond the handful of large, well-known players that everyone in the market is already competing for. This coverage area is a key differentiator for Baseten's broader compute strategy, so we're looking for the best possible person in this specific lane rather than a generalist. You'll own the full lifecycle of a sourcing relationship — from first outreach to ongoing management — not just the introduction. WHAT YOU'LL DO Build and maintain a comprehensive map of data center and powered land opportunities, with a particular focus on the long tail rather than the handful of major, oversubscribed players Own the full sourcing lifecycle for each relationship — from identifying and reaching out to new providers, through negotiation support, to ongoing relationship management — not just the initial introduction Develop and manage sourcing relationships across neoclouds, hyperscalers, brokers, and independent operators Quickly and independently evaluate new sites and spaces to determine fit and priority Prepare business cases and cost analysis to support new data center and powered land opportunities, partnering with Finance where needed Maintain accurate records of suppliers, contracts, and commercial terms so the team has a reli

Machine LearningAIGoProject Management
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 As a member of the Capacity Strategy & Operations team, you will sit at the intersection of supply intelligence, demand forecasting, and cross-functional execution, turning a complex, fast-moving hardware market into a predictable, reliable foundation for our customers and internal engineering teams. This is not a purely analytical role. You will own the end-to-end capacity planning process: from translating customer commitments and growth forecasts into concrete supply requirements, to coordinating fulfillment across vendors, finance, and the infrastructure team, to building the systems that make all of this repeatable and scalable. When supply is constrained and tradeoffs are unavoidable, you are the person in the room who can model the options, make a clear recommendation, and drive alignment fast. You are a strong fit if you have operated at the intersection of strategy and execution before — someone who is equally comfortable building a capacity model in a spreadsheet and running a cross-functional war room when a customer deployment is at risk. EXAMPLE INITIATIVES Demand-Supply Alignment Framework: Build and own the process that translates customer pipeline, signed commitments, and growth projections into a forward-looking GPU demand signal — so the team is never caught flat-footed when a customer scales faster than expected. Constrained Allocation Playbook: Define the decision framework for how Basete

Machine LearningAIGoExcel
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📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 We’re looking for a Recruiting Coordinator to help create a seamless, welcoming, and well-organized interview experience for every candidate who engages with our team. You’ll work closely with our recruiters to coordinate both virtual and in-person interviews, support executive involvement when needed, and ensure candidates have everything they need during throughout their interview process. This role is ideal for someone who thrives on operational excellence, loves solving logistics problems on the fly, and brings both warmth and precision to every interaction. RESPONSIBILITIES Work closely with recruiters and hiring managers to coordinate interview loops and debriefs for candidates and the internal team members conducting interviews Ensure every candidate has a smooth, well-communicated, and positive experience Manage logistics for onsite interviews, including candidate arrival and workspace setup Proactively identify and solve day-of issues, including last-minute changes or scheduling conflicts Communicate clearly and promptly with candidates and internal teams about interview logistics and updates REQUIREMENTS 1+ year of recruiting or HR experience Detail-oriented and operationally strong—you know how to keep things moving Clear and professional written and verbal communication skills Personable and warm—you're great at making candidates feel welcome and supported Ability to think on your feet and respond to

Machine LearningAIExcelLogistics
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 As a Global Capacity Manager focused on TPUs at Baseten, you will lead the "engine room" for our non-NVIDIA accelerator fleet, architecting, securing, and optimizing the Google Cloud TPU (and broader emerging accelerator) capacity that powers our customers' AI workloads. You'll own the end-to-end journey of capacity management for this fleet, from securing large-scale TPU pod allocations to building the automation that ensures reliable uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering, with a specific focus on the TPU ecosystem. You will act as the fleet orchestrator for Google's TPU architecture, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics as we diversify beyond NVIDIA. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the latest generation of TPU hardware, like Google's Trillium (v6e) architecture, and partnering closely with the Model Performance (MP) team to ensure workloads are tuned for TPU-specific execution. EXAMPLE INITIATIVES The TPU Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's TPU clusters, including pod slicing and topology planning Global Workload Orchestration: Bui

PythonAWSAzureGCP
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 We’re looking for a high-performing strategic finance professional to join our growing GTM Finance team. Our business grows with our customers' usage, which makes the finance function highly strategic at Baseten: growth, pricing, margin, and capacity decisions are business model decisions. You'll sit at the center of them, partnering directly with GTM leadership and reporting into a finance team with a seat at the table for the calls that shape the company's trajectory. This role is ideal for someone with 3 to 7 years of experience across strategic finance, investing, and/or investment banking who wants broad exposure to company-building inside a fast-scaling AI infrastructure company. Experience at a usage-based software company is a plus. RESPONSIBILITIES Own financial planning, forecasting, and budgeting processes for the GTM org Build and maintain financial models across revenue, S&M spend, headcount, and strategic bets Analyze the metrics that define a usage-based business – ARR, gross margin, consumption trends, retention, and GTM efficiency Partner with GTM leaders to set targets, evaluate growth initiatives, shape pricing, and design sales compensation Help prepare board materials, investor updates, and fundraising analyses Improve financial reporting, dashboards, and operational rigor so our infrastructure scales as fast as our revenue Work cross-functionally to turn ambiguous business questions int

SQLRestMachine LearningAI
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📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 As a Global Capacity Lead at Baseten, you will lead the "engine room" of the company, architecting, securing, and optimizing the global GPU fleet that powers our customers' AI workloads. You’ll own the end-to-end journey of capacity management, from securing multi-million dollar GPU clusters to building the automation that ensures 99.9% uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering. You will act as the fleet orchestrator for the world's most advanced chips, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the next generation of hardware, like NVIDIA’s Blackwell (B200) architecture. EXAMPLE INITIATIVES The B200 Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's first Blackwell GPU clusters. Global Workload Orchestration: Building "Multi-cloud Capacity Management" systems to move customer workloads seamlessly across regions to optimize cost and latency. Precision GPU Triage: Developing automated Go-based operators to identify, cordon, and repair unhealthy H100 nodes in under an hour. The Supply Chain of Intelligence: Partnering with lead

PythonAWSAzureGCP
B
📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -83%
Quick readStrong listing-quality and freshness signals

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 We're looking for a Delivery Director, Capacity programs for our on-premises data center builds and neo cloud (GPU cloud) delivery programs. This is a high-visibility, execution-critical role sitting at the intersection of infrastructure engineering, capacity planning, vendor/partner management, and customer delivery. You will own the end-to-end delivery lifecycle for large-scale compute infrastructure — from initial site/capacity commitments through power, networking, and hardware bring-up, to production-ready GPU/compute capacity landing in the hands of internal teams or customers. You'll be the person who turns ambitious infrastructure roadmaps into predictable, on-time, delivery. RESPONSIBILITIES Own delivery of on-prem infrastructure builds — colocation expansions, power/cooling readiness, rack-and-stack, network fabric bring-up, and hardware acceptance testing — coordinating across colo providers and partners, network engineering, hardware ops, and vendor teams. Drive neo cloud delivery programs — manage capacity delivery from GPU cloud and neo cloud partners (e.g., colocation/bare-metal/GPU cloud providers), including contract milestones, capacity ramps, SLAs, and go-live readiness. Build and maintain master delivery schedules across concurrent, multi-site, multi-vendor programs, integrating power/shell timelines, hardware lead times, logistics, and software/platform readiness into a single critical path.

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