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Software Engineer - Training Infrastructure

Baseten · Hybrid

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MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last seen by MeritLog September 12, 2026Source: AshbySource version: ashby-public-job-posting-v1

Source: the employer's Ashby job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
San Francisco
Occupation
Software Developers(O*NET 15-1252.00)

What the role asks for

What you'd do

  • 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

What they're asking for

  • Bachelor’s degree or high in Computer Science or related fieldEducation
  • Proficiency in Go, withSkill
  • Deep expertise with Kubernetes in production environmentsSkill
  • Advanced understanding of distributed systems concepts and performance tuningSkill
  • Proven experience designing observability systemsSkill
  • Experience with ML/AI workloads and MLOps platformsSkill
  • Experience with distributed storage systemsSkillPreferred
  • Python experience a plusSkillPreferred
  • Extensive experience with major cloud providers (AWS, GCP) and neo-cloud providers (Crusoe, DigitalOcean, Nebius)SkillPreferred
  • Experience with workload orchestration platforms like Temporal or AirflowSkillPreferred
  • 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).SkillPreferred
  • Experience developing AI products, tooling, or agentsSkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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 https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Software Engineer at 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 EXAMPLE INITIATIVES Take a look at what we’ve built so far: - Overview of the product so far https://www.baseten.co/blog/baseten-training-is-ga/#training-is-now-ga - Training docs overview https://docs.baseten.co/training/overview - Story of the Training product https://www.baseten.co/blog/a-q-a-from-inference-to-training-the-inside-story-of-baseten-s-newest-product/ - Research we've done https://www.baseten.co/resources/research/ 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 high in Computer Science or related field - 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 - 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).

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