Post-Training Research Engineer

Baseten
San Francisco
Workplace: HybridFull timeUSD 200,000 - 275,000 annuallyFunction: Education & TrainingSkills: ["Communication","Collaboration","Problem-solving","Creativity"]

Join Baseten’s Post-Training team as a Research Engineer focused on building in-house tooling to support post-trained models. You’ll work across the stack on systems like Kubernetes, storage and networking, and PyTorch distributed tensor computation to train and optimize transformer models at scale, profiling distributed GPU performance and applying advanced ML techniques.

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Baseten
Baseten
4 months ago

Post-Training Research Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Join Baseten’s Post-Training team as a Research Engineer focused on building in-house tooling to support post-trained models. You’ll work across the stack on systems like Kubernetes, storage and networking, and PyTorch distributed tensor computation to train and optimize transformer models at scale, profiling distributed GPU performance and applying advanced ML techniques.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Education & Training

Key Responsibilities

  • •Build in-house tooling and infrastructure to support post-training workflows and model training at scale
  • •Work across the stack on systems-level topics (Kubernetes, storage, networking) and GPU kernel optimization to improve performance
  • •Collaborate with researchers to derive specifications and implement efficient transformer training and inference workflows
  • •Profile and optimize distributed GPU programs and perform roofline analysis on transformer setups
  • •Contribute to tooling and processes that enable Baseten customers to deploy high-quality post-trained models

Pay and Benefits

Salary: USD 200,000 - 275,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceVisionDental401kPaid Leave

Key Requirements

  • •Deep understanding of modern ML techniques and tools for training transformers
  • •Advanced experience with a tensor/array computation library such as PyTorch, TensorFlow, or Jax
  • •Detailed understanding of transformer training parallelism strategies (data/sharded/tensor/pipeline/context parallelism)
  • •Experience profiling and improving the performance of distributed GPU programs in PyTorch or similar
  • •Familiarity with HPC and distributed computing platforms like Slurm, Ray, Kubernetes, and Dask
Experience:Machine learningAIResearch
Skills:CommunicationCollaborationProblem-solvingCreativity
Languages:English
Tech Stack:PyTorchTensorFlowJaxKubernetesSlurmRayDaskGPUGPUDirectInfinibandRoCE

Company Brief

Baseten
Baseten provides an inference-first ML infrastructure platform that lets engineering and ML teams deploy, serve, and scale machine-learning models with optimized performance, autoscaling, and GPU-backed hosting for production AI applications. ([crunchbase.com](https://www.crunchbase.com/organization/baseten?utm_source=openai))
Industry: AI & Machine Learning
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2019
Glassdoor
Glassdoor: 5.0
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