Jobs in United States

Partner Manager in United States

4,992 active opportunities · Updated October 2026

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

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 are looking for an Account Executive to join our dynamic team. This role is a great fit for those with sales experience looking to grow within a high-growth startup environment. As an Account Executive, you will prospect and close new business alongside our founders and Marketing team. You’ll consult with our existing customer base and prospective customers to build meaningful relationships and shape our product and go-to-market roadmaps. RESPONSIBILITIES Help build the foundation and processes for customer-facing teams at Baseten Lead, negotiate, and execute new sales opportunities for Baseten In partnership with the marketing and BDR team, develop a strong sales pipeline to support quarterly and annual sales targets Establish and maintain relationships with key stakeholders within sales accounts Work cross-functionally to improve the customer experience and ensure sales effectiveness REQUIREMENTS 1-3 years of sales experience in a SaaS business Experience in selling to technical audiences Experience with developer/machine-learning tooling preferred, but not required Proven ability to close complex sales cycles Proficiency with sales and marketing automation tools Interest in working at an early-stage, fast-paced startup BENEFITS Competitive compensation, including meaningful equity. 100% coverage of medical, dental, and vision insurance for employee and dependents Flexible PTO policy including company wid

RestMachine LearningAIGo
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-source ML models, we look forward to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure. Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues. Apply and scale optimization techniques across a wide range of ML models, particularly large language models. Collaborate with a diverse team to design and implement innovative solutions. Own projects from idea to production. REQUIREMENTS Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. Experience with one

PythonDockerKubernetesRest
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 As a Site Reliability Engineer at Baseten, you'll define and codify the gold standards of day 2 operations for our ML infrastructure platform. You'll envision and build robust systems, processes, automations, and observability tooling that keep our platform reliable at scale — and that empower the broader organization to operate confidently. You'll work closely with engineering, forward-deployed and product teams: learning from recurring failure patterns, turning tribal knowledge into automated mitigations, and raising the operational floor for the entire company. EXAMPLE INITIATIVES You'll work on projects like these as part of the SRE team: Improve Baseten SRE Practices, by instrumenting SLOs and SLIs, improving alerting and observability for all services. Building AI-assisted tooling for incident triage and response. RESPONSIBILITIES Own the reliability of Baseten's multi-cloud Kubernetes infrastructure, including incident response, post-mortems, and remediation tracking. Build and maintain observability infrastructure — metrics, logging, dashboards, and alerting — as code. Author, validate, and improve runbooks for recurring failure patterns, ensuring they're structured for low-context, safe execution. Identify high-frequency failure patterns and convert them into automated mitigations or self-healing automations. Diagnose and resolve runtime issues related to latency, memory behavior, GPU utilization, con

KubernetesGitMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 Baseten's engineers want to work in an AI-first way. What's missing isn't enthusiasm — it's the platform underneath it. Today everyone assembles their own agent config, context files, and MCP servers, so the good patterns stay trapped in individual setups instead of becoming defaults everyone inherits. You'll build that platform: the agent configurations tuned to our monorepo, the context and tooling layer that makes agents competent in our codebase, the evals that tell us which approaches actually work, and the rollout mechanics that get a new engineer productive with agents in week one. You are not here to mandate how engineers use AI — you're here to make the good path the easy path. Success looks like teams adopting what you build because it beats what they'd cobble together themselves, not because a policy requires it. Platform engineer, not AI evangelist. Ship infrastructure, measure it, kill what doesn't work, let adoption be the referee. The playbook for AI-first SDLC doesn't exist at any company yet. You'll write ours. WHAT YOU'LL BUILD Agent substrate — Repo-level context infrastructure that makes agents competent in our codebase ( CLAUDE.md/AGENTS.md conventions, architecture and domain context, and the tooling to keep it accurate as code moves). Internal MCP servers giving agents scoped access to CI, observability, incident tooling, deployment state, and docs. Shared skills, subagents, and hooks th

PythonDockerKubernetesCI/CD
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Impl

AWSMachine LearningAIC++
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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. ABOUT BASE LABS Base Labs is a research lab pushing the frontier of open-source LLMs. We think intelligence should be democratized, not controlled by a handful of closed labs and we think very few teams are actually positioned to do something about that. Backed by Baseten's training and inference infrastructure, we have the compute, resources, and talent to take on hard problems at the frontier and open-source what we learn along the way. Our mission is to help build a world where intelligence isn't concentrated, but spread across an ecosystem of models that anyone can build on. That mission shapes what we choose to work on, how we work on it, and who we want in the room. We are accepting applications on a rolling basis for our first cohort of Base Labs Fellows, which is expected to start in late September. Apply using this link. BASE LABS FELLOWSHIP OVERVIEW The Base Labs Fellowship is designed to give researchers exposure to what frontier research looks like in industry. We provide funding, mentorship, and full support to our fellows, with the goal of producing rigorous, published research that shapes both the open-source ecosystem and Baseten's technical roadmap. We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in Sept 2026 and beyond. WHAT TO EXPECT 3 months of full-time research from our San Francisco office A dedicated 1:1 mentorship

Machine LearningAIGo
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 Baseten is seeking talented and experienced Software Engineers to join our Platform team within the Infrastructure organization. As a senior member of Baseten's Platform Team, you will own the systems that let every engineer at Baseten prove their code works before it reaches production. Our product runs mission-critical AI inference for customers who measure downtime in dollars per second, which means our internal bar for correctness, performance, and failure tolerance has to be exceptional. Your focus is the full testing stack: fast and reliable unit test tooling, integration harnesses that spin up realistic environments on demand, load and performance testing for GPU-backed inference workloads, and resilience testing that deliberately breaks things so our customers never have to find out what happens when a node dies mid-request. This is a builder role with org-wide leverage. You won't be writing tests for other teams — you'll be building the frameworks, harnesses, and feedback loops that make writing good tests the path of least resistance, and you'll set the standards for what "well-tested" means at Baseten. RESPONSIBILITIES Own Baseten's testing strategy end to end — define the standards, the tiers, and the tooling that engineering teams build against. Build and maintain unit, integration, load and performance testing frameworks Design end to end test infrastructure that provisions realistic dependencies

PythonDockerKubernetesCI/CD
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 Baseten is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. As an early member of the Observability Team, you will be pivotal in building and shaping the observability experience for our internal and external customers. By joining this team, you’ll have a direct impact on the reliability and operational excellence of Basetens product systems. As Baseten scales its infrastructure across different cloud providers and diverse hardware, the volume and complexity of operational data is growing by orders of magnitude. This team is responsible for building high-throughput ingest pipelines, cost-efficient storage, and agentic diagnostic tools to ensure that we can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become more complex. RESPONSIBILITIES Design and build scalable telemetry ingest and storage pipelines for metrics, logs, and traces across Baseten’s multi-cloud infrastructure Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliabi

PythonRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 Baseten is seeking talented and experienced Software Engineers to join our Platform team within the Infrastructure organization. As an early member of Baseten's Platform Team, you will be pivotal in building internal infrastructure to support our engineering organization. You will own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across Baseten to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. If you are passionate about elegant solutions—like streamlined monorepos, lightning-fast CI pipelines, and thoughtfully designed shared libraries—you'll thrive at Baseten. RESPONSIBILITIES Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces,

PythonKubernetesGitRest
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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 Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

KubernetesMachine LearningAIGo
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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. We are looking for an engineer with strong experience in machine learning and solid foundations in maths and computer science to join our growing Post-Training team at Baseten. Custom models are instrumental to the success of Baseten customers. By inference volume, the overwhelming majority of traffic at Baseten is to and from models that have been post-trained in some way, whether that be through reinforcement learning, supervised finetuning, a recent technique from the literature, or an in-house research technique from Baseten. The Post-Training team is responsible for the success of our customers’ post-trained models, and we employ a wide array of techniques to produce models that are more efficient and higher quality than even the biggest closed source models for the customer’s specific needs. Your role as a research engineer is to build the in-house tooling to support all of this. We care about training a wide spectrum of different model architectures with a variety of techniques efficiently and at scale. At times this involves zooming deep into a particular technical topic, but more often if involves working across the stack as a whole - systems-level concepts like Kubernetes, cgroups, storage systems, and networking topologies, as well as PyTorch distributed tensor computation, and GPU kernels. RECENT RESEARCH Dense, on-policy or both? Repeated kv cache for long-running agents Distillation without the dark – rep

KubernetesMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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

KubernetesRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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: Baseten’s Model Performance (MP) team is responsible for ensuring the models running on our platform are fast, reliable, and cost‑efficient. As part of this team, you’ll focus on Model APIs — the infrastructure powering our hosted API endpoints for the latest open‑source models. This work spans distributed systems, model serving, and developer experience. You’ll join a small, high‑impact team operating at the intersection of product, model performance, and infra, helping to define how developers interact with AI models at scale. RESPONSIBILITIES: Design, build, and operate the Model APIs surface with focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling and multi-modal serving Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA operators, tune memory allocation patterns for maximum throughput and optimize communication patterns across multi-GPU setups Productionize performance improvements across runtimes with deep understanding of their internals: speculative decoding implementations, guided generation for structured outputs, custom scheduling and routing algorithms for high-performance serving Build comprehensive benchmarking frameworks that measure real-world performance across different model architectures, batch sizes, sequence lengths, and hardware configurations Productionize performa

KubernetesMachine LearningAIGo
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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

PythonCI/CDGitRest
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.4%

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. At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations. THE OPPORTUNITY Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed. In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts. WHAT YOU'LL DO Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack,

PythonKubernetesMachine LearningAI
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