Software Engineer - Training Infrastructure

Baseten; San Francisco (CA); On-site; USD 165,000 - 330,000; Full time

Benefits offered by this job

Competitive compensation, including meaningful equity

100% coverage of medical, dental, and vision insurance

Flexible PTO policy and paid parental leave

Company-facilitated 401(k)

Job summary

Baseten is looking for a Software Engineer to join their Training Infrastructure team in San Francisco. You'll architect and lead the development of the training platform, enabling developers to deploy and monitor workloads efficiently. The ideal candidate has a Bachelor's degree, strong proficiency in Go, extensive experience with Kubernetes, and knowledge of ML workload management. Benefits include competitive compensation, medical insurance coverage, and a flexible PTO policy.

Qualifications

• Bachelor's degree or higher in Computer Science or related field.
• Proficiency in Go, with Python experience a plus.
• Deep expertise with Kubernetes in production environments.
• Extensive experience with major cloud providers (AWS, GCP).
• Advanced understanding of distributed systems concepts.
• Proven experience designing observability systems.
• Experience with ML/AI workloads and MLOps platforms highly valued.

Responsibilities

• Design and architect scalable infrastructure systems for ML training platform.
• Partner closely with developers and research engineers.
• Drive long‑term improvements for reliability and velocity of development.
• Lead technical discussions and mentor junior engineers.

Skills

Proficiency in Go

Experience with Python

Deep expertise with Kubernetes

Experience with major cloud providers (AWS, GCP)

Advanced understanding of distributed systems

Experience with ML/AI workloads

Education

Bachelor's degree or higher in Computer Science or related field

Job description

Baseten powers mission‑critical inference for the world’s most dynamic AI companies, such as 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’ve recently raised $300M in Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction.

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 that enables developers to deploy, scale, and monitor workloads with high performance and reliability. You’ll own scheduling, storage, networking, reliability, and observability of technical systems in the training stack.

EXAMPLE INITIATIVES

• Overview of the product so far
• Training docs overview
• Story of the Training product
• Research we've done

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 improve 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
• Proficiency in Go, with Python experience a plus
• Deep expertise with Kubernetes in production environments
• Extensive experience with major cloud providers (AWS, GCP) and emerging cloud providers (Crusoe, DigitalOcean, Nebius) a plus
• Advanced understanding of distributed systems concepts and performance tuning
• Proven experience designing observability systems
• Experience with ML/AI workloads and MLOps platforms highly valued

NICE TO HAVE

• Experience with distributed storage systems
• 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
• 100% coverage of medical, dental, and vision insurance for employees 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

Equal Opportunity Statement

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 (e.g., the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Compensation Range: $165K - $330K