Machine Learning Infrastructure Engineer Jobs

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 Strategic accounts at Baseten are the largest and fastest-growing AI companies in the world. These are the teams defining the future of what AI products and services look like. These accounts can scale rapidly from one token to billions of tokens in a matter of weeks. This role owns these relationships, working directly with founders and engineering leaders on mission-critical and large-scale-AI problems in production—and shaping what we build next. This is a highly technical sale. You’ll trade opinions on the latest open-source model releases, run fast and nuanced evaluations alongside customer engineering teams, and often pulling in SMEs from applied research to infrastructure engineers to win. You’ll bring tight sales fundamentals and process discipline, while maintaining flexibility and creativity in how you run each cycle. This role is pioneering what sales looks like at the bleeding-edge of technology sales. This is a front row seat to the most consequential decisions made at the forefront of Artificial Intelligence. There is no faster place to learn and make an immediate impact. RESPONSIBILITIES Own a focused portfolio of high-growth, strategic AI-native accounts end to end — from technical evaluation and initial workload landing through expansion as inference usage scales. Lead technical evaluations and complex, multi-stakeholder sales cycles from first conversation through close. Bring strong sales fund

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 Strategic accounts at Baseten are the largest and fastest-growing AI companies in the world. These are the teams defining the future of what AI products and services look like. These accounts can scale rapidly from one token to billions of tokens in a matter of weeks. This role owns these relationships, working directly with founders and engineering leaders on mission-critical and large-scale-AI problems in production—and shaping what we build next. This is a highly technical sale. You’ll trade opinions on the latest open-source model releases, run fast and nuanced evaluations alongside customer engineering teams, and often pulling in SMEs from applied research to infrastructure engineers to win. You’ll bring tight sales fundamentals and process discipline, while maintaining flexibility and creativity in how you run each cycle. This role is pioneering what sales looks like at the bleeding-edge of technology sales. This is a front row seat to the most consequential decisions made at the forefront of Artificial Intelligence. There is no faster place to learn and make an immediate impact. RESPONSIBILITIES Own a focused portfolio of high-growth, strategic AI-native accounts end to end — from technical evaluation and initial workload landing through expansion as inference usage scales. Lead technical evaluations and complex, multi-stakeholder sales cycles from first conversation through close. Bring strong sales fund

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.

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, Washington D.C., London and Amsterdam. We lead complex technical programs that help Plaid scale its engineering platform. We partner across Engineering, Infrastructure, Data, Security, ML, Legal, and Product to deliver company-wide technical initiatives that improve reliability, scalability, and developer productivity. You'll lead strategic technical programs from planning through execution. You'll partner with engineering leaders to align stakeholders, manage dependencies, drive decisions, and ensure successful delivery of complex initiatives. You'll work across a variety of technical domains, adapting quickly to new challenges and helping teams execute effectively. As a Technical Program Manager, you will lead high-impact, cross-functional initiatives. As a generalist, you may work on a variety of programs. An example is one that strengthens Plaid's data and machine learning platforms. You will partner with engineering, product, data, legal, privacy, and business stakeholders to drive complex technical programs from planning through execution. Your work will help improve data governance, modernize machine learning infrastructure, and accelerate the adoption of trusted, high-quality datasets that power analytics, artificial intelligence

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. PRODUCT AT BASETEN Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer-obsessed, and moves fast. We're building the product function now, and you'd be one of the people who defines it. You'll work directly with our founders and with some of the best systems and infrastructure engineers in the world, and you'll set the standard for what product looks like here. You earn trust by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences. THE ROLE The largest, most demanding Enterprises are starting to run on Baseten and they come with a range of security, compliance, and procurement requirements. Today that readiness is assembled deal-by-deal. You'll own the enterprise-readiness surface end to end and turn it into product: the deployment options customers can choose and buy, compliance posture they can trust, access and security controls their IT teams require, and the billing and spend controls their finance teams expect. What does a complete Baseten Enterprise Product offering look like? RESPONSIBILITIES Drive the Enterprise Readiness customer experience end to end: Partner with GTM and Enterprise Engineering to make "enterprise-ready" a platform-wide capability, not a deal-by-deal scramble. Outcome: readiness becomes a supported, priced product instead of bespoke work asse

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

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 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 l

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: We are looking for a Machine Learning Engineer on our Trust & Safety Engineering team, to build and operate the production systems that detect and stop abuse on the platform at internet scale. This is an engineering-first role, roughly 80% writing and shipping production code (services, pipelines, and infrastructure) and 20% modeling, taking detection and classification approaches from prototype to hardened systems. This is a hybrid role based in San Francisco or New York City, with three days a week in the office. What you’ll do: Design, build, and operate production systems that detect and disrupt abusive behavior across the platform, with an emphasis on reliability, scalability, and observability Build and maintain machine learning (ML) infrastructure, including training pipelines, feature pipelines, serving infrastructure, and evaluation frameworks Ship large language model (LLM) and classical ML approaches for abuse detection and classification, turning prototypes into maintainable code Own systems end to end, from integrating a model into the platform through deployment, monitoring, and iteration Work with security, product, and infrastructure teams to turn abuse patterns and detection logic into production systems What you need: 5+ years of software engineering experience building and operating production systems at scale Wrote production code in Python, plus JavaScript/TypeScript or Go Built and maintained ML infrastructure, such as training and serving pipelines, feature stores, or evaluation tooling Integrated LLMs in

A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Develop and maintain scalable artificial intelligence/machine learning (AI/ML) architectures and systems. Collaborate with data scientists, engineers, product teams, and Compliance to integrate AI/ML solutions into existing and new products. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies. Ensure compliance with industry standards and best practices in AI/ML. What’s required Bachelor's or master's degree in computer science, engineering, or a related field. 3-7 years of experience in AI/ML engineering, with a proven track record of successful project delivery. Strong expertise in machine learning frameworks and libraries, such as TensorFlow, PyTorch, and/or Scikit-learn. Proficiency in programming languages such as Python, Java, or C++. Excellent problem-solving skills with the ability to work independently and collaborativel

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Every request that hits Claude — from claude.ai , the API, our cloud partners, or internal research — depends on a set of decisions made before it ever reaches a model: where each request should be served and how much capacity each model needs right now. Getting those decisions right is crucial to satisfying throughput, reliability, and latency constraints. This group builds the control plane that makes those decisions for Anthropic's inference fleet and own the inference request path. This is a deeply technical group. The engineers here design placement and load-balancing algorithms, build quantitative models of demand, capacity, and system performance, improve latency across kernel, network, and framework boundaries, and reason carefully about how a change to the fleet ripples through everything that depends on it. You'll lead a strong group of ML platform, infrastructure, and distributed-systems engineers working alongside the teams that build our ML internals and cloud infrastructure. You need enough systems depth to make architectural calls, hire people who go deep, and see when a proposed change will ripple across the fleet. You're accountable for the health of the whole path from request to model: its efficiency, its reliability, and how well it evolves as models, hardware, and clouds change underneath it. Key responsibilities Own the technical roadmap for how the inference fleet is coordinated — where traffic goes, where capacity lives, how caches are placed, how fast the system reacts to demand, and the protocols that keep the control plane and the inference engines in sync Partner with the product, inference e

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 This role bridges infrastructure and product engineering: you'll build genuine partnerships across product, AI, and enterprise teams so that ownership is shared and velocity is never blocked by platform constraints. As Director, you'll set a forward-looking cloud vision, proactively align with stakeholders across the business, and ensure the platform scales for multi-shard, multi-region growth while meeting security and compliance commitments (SOC 2, business continuity/disaster recovery, and enterprise security frameworks). The Role: Cost Efficiency: Drive significant annual infrastructure savings by migrating data workloads to EKS and self-hosting key services such as OpenSearch. Ingress Convergence: Deprecate legacy frontend ALBs and consolidate to a single EKS-managed ALB per shard, unblocking faster deployments across the org. Coverage & Bench Depth: Eliminate single points of ownership across Networking, OpenSearch, and Terraform through cross-training and targeted hiring into coverage gaps. Stakeholder Alignment: Stand up a recurring alignment cadence with Product, AI, Enterprise, and Security so infra planning is driven by demand, not ad-hoc interrupts. Automation: Ship automated shard buildout via Backstage to remove manual toil from enterprise scaling. Reliability: Cut P0/P1 incidents attributed to Cloud Platform (DNS, ALB misconfiguration) through hardened ingress patterns and Terraform-policy guardrails, including blocking unauthenticated public endpoints. Roadmap Ownership: Deliver a roadmap covering Agent enablement, centralized IaC, and deployment rollout acceleration, tied to AI and

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 This role bridges infrastructure and product engineering: you'll build genuine partnerships across product, AI, and enterprise teams so that ownership is shared and velocity is never blocked by platform constraints. As a leader, you'll set a forward-looking cloud vision, proactively align with stakeholders across the business, and ensure the platform scales for multi-shard, multi-region growth while meeting security and compliance commitments (SOC 2, business continuity/disaster recovery, and enterprise security frameworks). You'll implement and drive the adoption of AI-powered tooling and autonomous agents within the infrastructure organization. The Role: Cost Efficiency: Deliver measurable annual infrastructure savings by executing the migration of data workloads to EKS and self-hosting key services. Ingress Convergence: Deprecate legacy frontend ALBs and consolidate to a single EKS-managed ALB per shard, unblocking faster deployments across the org. Coverage & Bench Depth: Eliminate single points of ownership across Networking, OpenSearch, and Terraform through cross-training and targeted hiring. Stakeholder Alignment: Stand up a recurring alignment cadence with Product, AI, Enterprise, and Security so infra planning is driven by demand, not ad-hoc interrupts. Automation: Ship automated shard buildout via Backstage to remove manual toil from enterprise scaling. Reliability: Cut P0/P1 incidents attributed to Cloud Platform (DNS, ALB misconfiguration, EKS) through hardened ingress patterns and Terraform-policy guardrails. Own incident response and RCA follow-through for the team. Roadmap Ownership

Zoox is building fully autonomous vehicles designed from the ground up for robotaxi service — and as we scale toward launch, our engineering infrastructure has to scale with us. We're hiring a Staff Site Reliability Engineer to own source control at Zoox, serving as the technical lead for the platform that every engineer depends on daily. This is a hands-on lead role. You'll set the direction for our Git-based monorepo, drive a restructuring of our Source Code management strategy, build the tooling that improves reliability and developer workflows, and partner with platform, security, and product teams to make source control a strategic asset rather than a bottleneck. The ideal candidate leads by building — with deep expertise in monorepo management (branching strategies, code review workflows, access controls, CI/CD) and a track record of improving developer productivity through code, not just guidance. You take ownership, measure what matters, and have the technical credibility to make decisions stick. In this role, you will: Own the technical strategy and roadmap for source control at Zoox. Plan and execute a strategic effort to scale source code management at Zoox: scoping, design, implementation, cutover, and validation, in partnership with security, platform, and engineering teams. Build and operate monorepo scalability improvements across repo structure, branch strategy, code ownership, large-file handling, and CI integration — including the scripts, hooks, and automation that make them stick. Develop the guardrails and developer-facing tooling that reduce toil for SRE and product engineering alike, measured by build times, merge friction, and interrupt volume. Set the technical bar through code reviews, design proposals, and pairing — and serve as the hands-on authority for source control decisions across Zoox engineering Qualifications 5+ years operating GitH

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researcher

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 an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containerizati