> Markdown version of [/jobs/ext/4620483-software-engineer-training-infrastructure](https://www.wearedevelopers.com/jobs/ext/4620483-software-engineer-training-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Software Engineer - Training Infrastructure

- **Company:** Baseten, Inc
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Cursor, Distributed Data Store, Distributed Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Digitalocean, Reinforcement Learning, Pytorch, DeepSpeed, Apache Spark, Reliability of Systems, Kubernetes, Information Technology, Machine Learning Operations, Megatron
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_35ce9310010976fac41e652e55abe0f7

## About the Role

* 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, * 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

## 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., 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., * 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