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Forward Deployed Engineer (Training)

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Forward Deployed Engineer (Training) in USA

  • Baseten
  • Full time
  • Email
  • San Francisco, CA

Responsibilities

  • Own each customer account’s technical outcomes, including workload design, operation, and scaling on Baseten.
  • Translate vague customer objectives into specifications, success criteria, proofs of concept, and production solutions.
  • Design evaluations and benchmarks, optimize inference, improve models through post-training, and rework evaluations as needed.
  • Triage mission-critical failures, own or route fixes, and remain accountable through resolution.
  • Build evaluation and deployment tooling, automation, recipes, and reference implementations to improve future engagements.
  • Shape the product roadmap and ship fixes and features into Baseten’s codebase.
  • Manage multiple accounts, sequence work, coordinate stakeholders, and communicate status and risk.

Requirements

  • Minimum 1–2 years of software engineering experience shipping and maintaining code in large production systems, ideally across the stack.
  • Experience debugging complex production issues using logs, metrics, and traces to identify root causes in unfamiliar systems.
  • Ability to own ambiguous technical problems, triage issues, make decisions under uncertainty, and involve system owners when appropriate.
  • Interest in working directly with customers and influencing product direction beyond pure engineering responsibilities.
  • Ability to communicate complex technical topics with customer engineers, customer leadership, and internal stakeholders.
  • Curiosity about AI inference and training and motivation to develop expertise in AI infrastructure.
  • Willingness to respond to customers outside regular working hours and participate in an on-call rotation.
  • Depth in infrastructure domains such as storage or networking, including InfiniBand or RoCE, is relevant.
  • Experience operating distributed compute platforms such as Kubernetes, Slurm, or Ray, especially for GPU workloads, is relevant.
  • Understanding of LLM architectures and inference engines such as vLLM, TensorRT-LLM, or SGLang is relevant.
  • Ability to profile and optimize GPU workloads in training or serving is relevant.
  • Hands-on experience with post-training techniques such as SFT and RL, or deep learning experience with PyTorch or JAX, is relevant.
  • Operational experience with on-call work, incident response, and debugging distributed systems under pressure is relevant.

Benefits

  • Competitive compensation including meaningful equity.
  • 100% medical, dental, and vision insurance coverage for employees and dependents.
  • Flexible PTO and a company-wide Winter Break, with offices closed from Christmas Eve through 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 and related learning and networking opportunities.

Salary: $200k - $400k/yr

Baseten

Baseten delivers critical inference solutions for AI companies, equipping them to seamlessly deploy advanced models at scale. Our unique blend of applied AI research and flexible infrastructure allows developers to accelerate their projects and meet demanding performance needs.

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