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. Join us and help build the platform engineers turn to ship AI products.
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
EXAMPLE INITIATIVES
Take a look at what we’ve built so far:
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 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.
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).
Skills Required
- Bachelor's degree in Computer Science or related field
- Proficiency in Go
- Experience with Kubernetes in production
- Experience with major cloud providers (AWS, GCP)
- Understanding of distributed systems concepts
- Experience designing observability systems
- Experience with ML/AI workloads and MLOps
Baseten Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baseten and has not been reviewed or approved by Baseten.
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Fair & Transparent Compensation — Feedback suggests pay targets the top of market with explicit ranges in postings and a stated aim to provide 90th percentile salaries with equity. Role descriptions emphasize competitive, experience-based pay bands and meaningful stock grants.
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Healthcare Strength — Healthcare is described as fully covered for medical, dental, and vision for employees and their families, reducing out-of-pocket costs. This comprehensive coverage is consistently highlighted alongside other core benefits.
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Leave & Time Off Breadth — Time off policies include unlimited PTO with a minimum expectation of at least four weeks, 16 paid company holidays, and a company-wide winter break. These elements indicate substantial protected time away from work.
Baseten Insights
What We Do
AI’s future won’t be a few massive models built by a handful of labs. It’ll be millions of specialized models embedded into every product, workflow, and experience by the people closest to the customer. The foundation of that future is inference. Inference determines the performance, reliability, latency, and economics of every AI product. For AI to scale globally, it must be as reliable, fast, cost-effective, and high-quality as possible. That’s why Baseten exists. Companies like Abridge, Cursor, Lovable, Notion, and OpenEvidence depend on Baseten to power mission-critical AI workloads in production.
Why Work With Us
We’re an interdisciplinary team of researchers, engineers, and operators building the Inference Cloud our AI future demands. We’re running at a hard systems problem that requires first-principles thinking across the entire stack. The bar is high. We work hard, move fast, and care deeply about quality.
