Baseten

Post-Training Research Engineer at Baseten (San Francisco, CA)

Baseten· San Francisco, CA· $200k–$275k·

Role details

Salary
$200k–$275k
Work type
Hybrid
Employment
Full-Time
Equity
Yes
Skills
Machine LearningPyTorchTransformer TrainingTensor ComputationGPU ProgrammingDistributed SystemsKubernetesSlurmRayDaskInfinibandRoCE
Benefits

Equity · Medical, Dental, And Vision Insurance · Flexible PTO · Company-Wide Winter Break · Paid Parental Leave · Fertility And Family-Building Stipend · 401(K) Facilitated By Company · Learning And Networking Opportunities

Baseten at a glance

AI inference platform for deploying, optimizing, and running machine learning models in production at scale.

Baseten runs trained AI models in production for other companies, handling the GPUs, autoscaling, runtime, and performance tuning so engineering teams get a fast, reliable API without operating the infrastructure themselves. It supports open source, custom, and fine tuned models across managed cloud, hybrid, and self hosted deployments.

$2B+ raised · latest: Series F · $1.5B · June 2026 (valuations of $13B and $11B across two tranches) · backed by Altimeter Capital, Conviction, Spark Capital, Sands Capital

Summary

Build in-house tooling and systems to support post-training machine learning models, including optimizing inference efficiency and scalability. The role involves working across the stack—PyTorch, distributed systems, and cloud infrastructure—to ensure customers achieve high-quality, efficient model deployment.

Job description

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 baseten.co/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn 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.

THE ROLE

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.

The Manifesto: labs.baseten.co/manifesto

RECENT RESEARCH

We don’t have a rigid set of skills, but here’s some of what we’re looking for:

  • A deep understanding of modern ML techniques and tools for training transformers
  • Advanced experience in a tensor/array computation library like PyTorch, TensorFlow, Jax, or similar
  • A detailed understanding of transformer training parallelism strategies like data parallelism, sharded data parallelism, tensor parallelism, pipeline parallelism, context parallelism
  • The experience and knowledge to profile and improve the performance of a distributed GPU program in PyTorch or a similar library
  • The ability to perform roofline analysis on a transformer training setup
  • A willingness to dive into messy problems, work with researchers, derive specifications by asking important questions, and execute
  • Familiarity with HPC and distributed computing platforms like Slurm, Ray, Kubernetes, and Dask
  • Familiarity with cluster networking technology like Infiniband, RoCE, GPUDirect
  • Solid fundamentals in operating systems concepts like processes, files, kernel drivers, containerisation, and networking protocols
  • A sense of creativity and willingness to ask difficult questions about our approach, assumptions, and tooling choices

BENEFITS

  • Competitive compensation, including meaningful equity
  • 100% coverage of medical, dental, and vision insurance for employee and dependents
  • Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
  • Paid parental leave
  • Fertility and family-building stipend through Carrot
  • Company-facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Why work at Baseten

  • Hard Technical Problems: Engineers work on the most challenging problems in modern infrastructure—model serving, low-level GPU optimization, networking, distributed systems, and observability. This is a high-agency, high-impact engineering environment.
  • High Growth Trajectory: The company is experiencing explosive growth (224% headcount increase, active hiring). This offers significant career acceleration and ownership opportunities.
  • Strong Engineering Culture: Founded by engineers, for engineers. The culture emphasizes "first-principles thinking across the entire stack" and a "customer-obsessed" mindset. The employer rating on compensation, culture, and work-life balance is rated highly (5.0).
  • Top-Tier Team & Investors: The team has strong talent density with hires from Meta, Stripe, Google, NVIDIA, and Databricks. Being backed by top-tier VCs provides stability and a clear long-term vision.
  • Hybrid/In-Office: Based in San Francisco with a strong in-person or hybrid culture common for fast-moving infrastructure startups.

Application questions