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Software Engineer

Baseten
Remote - San FranciscoUpdated 414d ago
Compensation
$165k–$330k
Published range
Location
Remote - San Francisco
Remote eligibility
Employment
Full-time
Mid-level
Role family
Engineering
AI / ML
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About the job

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.

The Role

As a Software Engineer on the Training Infrastructure team, you'll architect and lead development of our training platform, supporting top tier research engineers and model developers. You'll make key technical decisions for the infrastructure enabling developers to deploy, scale, and monitor their workloads with high performance and reliability. You'll own scheduling, storage, networking, reliability, and observability of technical systems in the training stack.

Responsibilities

  • Design and architect scalable infrastructure systems for our ML training platform (e.g. scheduling, storage, and networking)
  • Partner closely with developers and research engineers to translate complex training requirements into technical solutions
  • Design and architect a global training scheduler
  • Design and architect reinforcement learning systems and continuous learning pipelines
  • Drive long-term improvements to increase reliability of systems and velocity of development
  • Partner closely with SRE and Capacity teams to unlock state of the art training infrastructure
  • Make critical architectural decisions balancing performance with system reliability
  • Lead technical discussions and mentor junior engineers on infrastructure best practices
  • Contribute to long-term technical strategy and infrastructure roadmap

Requirements

  • Bachelor's degree or higher in Computer Science or related field
  • 5+ years of experience
  • Proficiency in Go, with deep expertise with Kubernetes in production environments
  • Advanced understanding of distributed systems concepts and performance tuning
  • Proven experience designing observability systems
  • Experience with ML/AI workloads and MLOps platforms

Nice to Have

  • Experience with distributed storage systems
  • Python experience a plus
  • Extensive experience with major cloud providers (AWS, GCP) and neo-cloud providers (Crusoe, DigitalOcean, Nebius)
  • Experience with workload orchestration platforms like Temporal or Airflow
  • Familiarity or experience with the open source training stack and frameworks (NCCL, PyTorch, Megatron, NemoRL, VeRL, Axolotl, HF Trainer) and distributed training techniques (FSDP, DeepSpeed)
  • Experience developing AI products, tooling, or agents

Benefits

  • Competitive compensation, including meaningful equity (U.S. only)
  • 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 (U.S. only)
  • Company-facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities

Skills & tags

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