AI Infrastructure Engineer Jobs in San Francisco

Anthropic

Our Sandboxing team builds the isolation layer that enables Claude to run code, use computers, or act as an agent. These systems are critical for executing code written by Claude for users, training and evaluating models, and supporting customer-deployed agents. The sandboxes must start rapidly, withstand adversarial code, and scale to handle numerous concurrent sessions. This role involves working at the intersection of the Linux kernel, virtualization, and container technologies, collaborating with research, product, and security teams to ensure both safety and performance.

$320k - $485k

Prime Intellect

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training/deployment for post-training at scale, including SFT, RL, and agent workflows. They are developing open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding and is looking for individuals passionate about frontier research, infrastructure, and go-to-market strategies in a nascent category.

$150k - $350k

Typeface

We help the world’s biggest brands move from brief to fully personalized campaigns — in days, not months. Founded by Abhay Parasnis and backed by Microsoft, GV, Salesforce, Lightspeed, Madrona and Menlo, we’re building category-defining technology at the intersection of creativity and AI with real impact. Join us to help shape the future of enterprise marketing. We're looking for a Staff Infrastructure Engineer to help lead core parts of our platform. You'll design, build, and scale the cloud infrastructure that powers our AI and GenAI workloads — ensuring reliability, security, and performance as we grow. This is your chance to shape the backbone of a platform trusted by Fortune 100 companies — building systems that are resilient, observable, and ready to scale with the next wave of AI.

$210k - $240k

NVIDIA is seeking a Senior Manager, Software Engineering to lead the evolution of its DevOps, Build Engineering, and Infrastructure team. This role involves building and guiding a high-performing engineering team responsible for the development, testing, verification, and release of core software for NVIDIA's CUDA driver, runtime, and related libraries in C++, Python, and Rust. The position offers hands-on leadership, focusing on people development, CI/CD, technical strategy, architecture, and end-to-end operational ownership, aiming to enhance the developer experience and platform for a global workforce.

$272k - $431k

NVIDIA Cloud Functions is seeking a motivated AI/ML Engineer with expertise in AI platform engineering at scale. The team develops and manages a serverless deployment platform designed to enable and scale AI inferencing workloads. This platform utilizes globally distributed orchestration of workloads on Kubernetes clusters backed by GPUs, operating in a cloud-agnostic manner. The role involves working with a team of innovative engineers to deliver a top-tier product for both external clients and internal NVIDIA teams, contributing to the forefront of cloud engineering paradigms for AI at scale.

$152k - $288k

Physical Intelligence

Physical Intelligence is building general-purpose AI for the physical world, developing foundation models and learning algorithms for robots and future physically-actuated devices. The Infrastructure team is central to this mission, building and operating the backbone for training state-of-the-art VLA models, large-scale simulation, and reliable deployment of intelligence across robot fleets. This role involves collaborating closely with researchers, robotics runtime, product, and platform engineers to ensure infrastructure scales from prototype to production-grade deployments.

Salary not listed

Luma is seeking a Software Engineer to own the serving of their AI models. This role involves integrating new model architectures into the inference engine, scaling deployments across thousands of machines, and optimizing the utilization of expensive GPU fleets while meeting internal service level objectives (SLOs). The work focuses on large-scale inference systems, including scheduling, fleet management, deployment pipelines, and ensuring reliability across diverse clusters and hardware providers. This position is ideal for a strong systems engineer comfortable with model serving and Kubernetes at scale, rather than those seeking pure modeling work.

$195k - $345k

Luma is seeking a Research Scientist / Engineer to build and optimize the distributed systems that train large-scale multimodal models across thousands of GPUs. This role focuses on advanced parallelism, training stability, and utilization across massive clusters, requiring deep expertise in distributed PyTorch and CUDA. The goal is to provide researchers with reliable, efficient, and scalable infrastructure for innovation.

$195k - $395k

Lambda, The Superintelligence Cloud, is seeking a Senior Systems Engineer to join their Enterprise AI Platforms team. This role focuses on building and scaling the internal systems that power Lambda's business, partnering across departments to implement tools, automate workflows, and ensure data integrity. You will be instrumental in designing, developing, and deploying software and services to enhance the availability, scalability, reliability, and efficiency of Lambda’s internal IT systems and platforms. The position requires a proactive approach to problem-solving, automation, and influencing the creation of new architectures for large-scale distributed systems, with a strong emphasis on AI infrastructure and tooling.

$206k - $275k

Crusoe

Crusoe is building the operating system for AI datacenters, managing one of the world's largest GPU fleets. This role focuses on building a unified platform that senses, reasons about, and acts on the entire fleet, moving beyond traditional operational methods to achieve fleet autonomy. The platform is designed as a product with an API-first approach, offering SDKs, paved paths, and a self-serve portal for internal teams. It comprises agents for telemetry and command execution, a distributed infra graph, a reconciliation core for state management, and domain services for various operational tasks. The goal is to create an autonomous system that continuously improves through a sense-correlate-reason-act-learn loop, reducing manual interventions and enabling other teams to build services and workflows efficiently.

$250k - $300k

Baseten

Baseten is seeking an Engineering Manager to lead a portion of their Inference Performance team. This team is responsible for accelerating and optimizing the performance of demanding AI workloads on GPUs. The role involves managing and growing a team of inference performance engineers focused on the inference engine and runtime, including areas like kernels, scheduling, batching, KV-cache management, and speculative decoding. It's a hands-on technical leadership position where you will define the team's direction, solve complex problems, and contribute technically to GPU performance while also focusing on hiring, developing, and supporting your team members. Your team's work will directly impact customer model inference speed and serving efficiency, and you will play a key role in shaping the team's structure as it scales.

$240k - $270k

Reducto

Reducto is seeking a Software Engineer for its Platform team to own the infrastructure behind the company's core API. This role involves ensuring document understanding systems are fast, reliable, and cost-efficient at scale. You will work across Python services, queues, model-serving, Kubernetes, observability, and developer tooling to enhance the platform's robustness. This is a high-leverage infrastructure position for someone who has built and operated production systems, prioritizes latency, reliability, and cost, and is adept at using modern LLM coding tools.

$200k - $325k

Join our Conversation Engine team to scale and optimize a cutting-edge Generative AI product that provides instant assistance to enterprise users. You will work at the core of Moveworks' Generative AI product, focusing on scaling and optimizing it for the enterprise solution space. We encourage innovative ideas to solve unsolved problems, collaborating closely with machine learning experts and cross-functional teams to rapidly iterate on new ideas and leverage user behavior data. Your challenge will be to scale and optimize our conversation engine to support hundreds of millions of users across multiple chat channels and use cases, enhancing our end-to-end product infrastructure with engineering quality and robustness.

$176k - $308k

Databricks

At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems by building and running the world's best data and AI infrastructure platform. As part of the AI Platform team, you will build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search. You will be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations, and we are building the infrastructure that powers the next generation of AI.

$166k - $225k

Sierra

Sierra is seeking a Software Engineer for its Inference team to build the systems that power their AI agents. This role focuses on making foundation models fast, reliable, and efficient at scale. You will define the inference architecture, working on systems for serving, routing, capacity management, and optimization for latency, reliability, and cost. This is a systems-first role at the intersection of distributed infrastructure and AI, requiring strong distributed systems fundamentals and experience with complex systems problems.

$230k - $390k

Baseten

Baseten powers mission-critical inference for leading AI companies, enabling them to bring cutting-edge models into production. We are seeking distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform ensures customers can deploy and operate advanced models with industry-leading performance, scalability, and reliability. You will work across the entire stack, from the developer experience for model deployment to the systems orchestrating Kubernetes and routing traffic efficiently, ensuring every model on our platform is fast, reliable, and cost-efficient.

$180k - $360k

Modal is building a new infrastructure layer for AI, focusing on the demands of AI workloads that previous infrastructure couldn't support. Our platform provides instant GPU access, sub-second container starts, and native storage, enabling customers to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We are experiencing rapid growth, with a significant increase in annualized run rate and a recent Series D funding round. Our team comprises experienced engineers and researchers from diverse backgrounds, including creators of popular open-source projects and academic researchers.

$220k - $300k

Cerebras

Cerebras Systems is seeking a senior software engineer to build and scale the platforms and tools used to monitor and manage its growing fleet of AI clusters across multiple data centers. This role involves owning substantial engineering work across backend services, operational tools, and user-facing applications. You will collaborate with various teams, including Cluster Operations, infrastructure, inference, security, and data center teams, to translate operational challenges into reliable, scalable software solutions. The goal is to ensure fleet health, efficient issue response, and continuous compute capacity availability.

Salary not listed

Together AI

Together AI is seeking a Staff Platform Infrastructure Engineer to lead service and platform infrastructure strategy across the engineering organization. This is a hands-on technical leadership role with the opportunity to establish a new team and define the standard for how services are built and operated. You will provide a stable, scalable service infrastructure foundation for mission-critical product and platform teams, focusing on reliability, repeatability, and ease of adoption. You will own and evolve crucial shared infrastructure, roll out new patterns and platform capabilities, and ensure services are built on company-wide foundations.

$240k - $280k

NVIDIA DGX Cloud provides AI services and endpoints for research and production workloads. We are seeking a Senior Production Engineer to develop software and automation that ensures these services are reliable, scalable, and safe to operate. The Production Engineering team focuses on large-scale distributed systems, including internal and external model endpoints, regional control plane services for workload orchestration and request routing, and the GPU/CPU compute infrastructure for inference and agentic workloads. Our work encompasses Kubernetes clusters across various cloud environments (AWS, Azure, Google Cloud, partner clouds) and on-premises deployments.

$184k - $357k

Join us as we build the next generation of enterprise search infrastructure powering AI agents. Our mission is to evolve from traditional product-specific search systems into a composable, agent-native platform that enables agents and applications to discover, retrieve, reason over, and recommend information across heterogeneous enterprise data sources. As a Senior Staff Engineer, you will be the technical owner for foundational search infrastructure that serves as the backbone of our agentic platform. You will drive the architecture, scalability, and evolution of core indexing and retrieval systems while partnering closely with Search Ranking, ML, Platform, and AI teams to deliver production-grade search capabilities that power agent experiences across the company.

$191k - $334k

d-Matrix

d-Matrix is seeking a Sr Staff Site Reliability Engineer to join their AI Infrastructure team. This role is crucial for owning the infrastructure layer that powers all engineering teams and customers, encompassing colocation facilities, on-premises GPU clusters, cloud environments, and platform services. You will be responsible for reliability, automation, and observability across these diverse environments, managing systems end-to-end from provisioning to incident response. This is a hands-on position focused on building and operating real infrastructure, collaborating with hardware and software teams on CI/CD, QA, and HPC workloads, and supporting customer-facing deployments.

$175k - $265k

Anthropic

Anthropic is building reliable, interpretable, and steerable AI systems to be safe and beneficial for users and society. The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences across AWS, GCP, Azure, and other cloud providers. This involves owning the end-to-end product on each platform, from API integration and intelligent request routing to inference execution, capacity management, and operations. Engineers on this team are highly leveraged, driving multiple revenue streams while optimizing compute resources. The role requires product-minded backend engineers who can navigate platform differences, design cross-provider services and abstractions, and make architectural decisions for reliability and cost-effectiveness at massive scale. The work directly contributes to increasing service scale, accelerating the launch of new models and features, and ensuring LLMs meet rigorous safety, performance, and security standards.

$320k - $485k

Anthropic

The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences of developers and enterprise companies across major cloud platforms like AWS, GCP, and Azure. Within this team, the model & inference launch team focuses on the validation pipeline for inference servers and load balancers. This critical infrastructure work ensures that every inference change, including new model launches and performance improvements, is deployed with correctness, performance, and reliability. The goal is to make validation fast, cost-effective, and trustworthy, directly impacting how quickly advanced models and features reach users on all cloud platforms and how efficiently compute resources are utilized.

$320k - $485k