3 months ago
Base Salary
$165k - $330k/yr
Responsibilities
- Own the Capacity product end to end, including scoping, design, implementation, and iteration based on internal stakeholder feedback.
- Translate operational requirements from Capacity, Sales, and SRE teams into clean product experiences.
- Build and maintain full-stack features across UI surfaces, APIs, and backend services.
- Identify and eliminate workflow bottlenecks and manual processes across the capacity lifecycle through tooling.
- Instrument systems with observability and monitoring so issues are identified before becoming incidents.
- Partner with SRE and Infrastructure teams to ensure Capacity reflects the operational state of the fleet.
Requirements
- Bachelor's degree or higher in Computer Science or a related field.
- 5+ years of software engineering experience, including meaningful experience owning a product or internal platform end to end.
- Strong full-stack proficiency with experience in NextJS, JavaScript, Postgres, Drizzle, Tailwind, and AWS.
- Experience working directly with non-engineering stakeholders to understand requirements and make product decisions.
- Experience building internal tooling, operational platforms, or developer infrastructure, particularly in high-growth or infrastructure-heavy environments.
- Ability to take high ownership, identify problems, fix them, and follow through.
- Interest in AI/ML infrastructure; familiarity with GPU infrastructure or capacity planning is a meaningful plus.
- Experience with SST.dev is preferred but not required.
Benefits
- 100% employer coverage of medical, dental, and vision insurance for the employee and dependents.
- Flexible paid time off, including a company-wide Winter Break from Christmas Eve through 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 and learning and networking opportunities.
Tech Stack
Categories
About Baseten
Baseten builds an AI inference platform that provides tooling, infrastructure, and hardware to deploy, scale, and serve machine-learning models in production. The company sells managed model serving and developer tooling to software teams at AI product companies, with customers including Notion, Abridge, Writer, and Cursor. Privately held and headquartered in San Francisco, it focuses on high-availability, globally distributed inference for production workloads.