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Infrastructure Engineer - Data Platform

TypeSafe AI
San Francisco, USA
Full-time
Senior · 5+ years experience
Onsite
USD 180000-280000 yearly / year
Discovered 1 months ago
PythonTypeScriptNext.jsTailwind CSSKubernetesClaude Code

Full Job Posting

About the Role

As a data infrastructure engineer, you will build the internal data platform and tooling that powers TypeSafe’s model training, evaluation, and experimentation. The systems you build will sit on the critical path of how we acquire data, evaluate model behavior, and improve our models through tight iteration loops. This data infrastructure is where much of the leverage in modern AI systems comes from!

This role focuses on building the developer-facing systems that make working with large datasets and model outputs easy, safe, and scalable.

Our tech stack is primarily Python. We also use TypeScript, Next.js, and Tailwind CSS for frontend, with Kubernetes for orchestration. We empower developers to use any tooling they find helpful for getting their job done, including Claude Code and Cursor.

Responsibilities

  • The role is wide ranging and you will wear many hats. Responsibilities include:
  • Design and build internal tools for managing datasets, model outputs, and evaluation results
  • Create reliable systems for dataset versioning, lineage, and reproducibility
  • Develop abstractions and APIs that allow research and product teams to interact with data without needing to understand underlying infrastructure
  • Build tooling that accelerates data acquisition, labeling, curation, and analysis
  • Create observability and debugging tools that make it easy to understand how data flows through training and evaluation systems
  • Collaborate closely with research, product, and infrastructure teams to ensure data systems support rapid experimentation while maintaining correctness and reliability

We expect that you

Are responsible, ownership-inclined, and a team player – you believe there is no such thing as “other people’s code”

Enjoy building tools and abstractions that improve developer productivity

Have experience designing data systems or internal developer platforms

Care deeply about correctness, reliability, and maintainability in systems that handle critical data

Collaborate well with others on technical and product design, advocating for what you need and adjusting to changing requirements

Are comfortable working in ambiguous problem spaces and building systems from first principles

Are mission aligned and excited to go all-in

Love being part of a team

We Are Hoping That You

Have previously built big things

Have 5+ years of professional software engineering experience (3+ years working on backend, data infrastructure, or ML systems)

Have experience designing systems that acquire, transform, and manage large datasets efficiently

Have experience with large-scale data analysis and experimentation

Have experience working closely with researchers or ML engineers to translate data needs into scalable systems

Have experienced LLMs’ capabilities and limitations from implementing them in the past

Life at TypeSafe

We’re a small, flat, close-knit team dedicated to real-world impact preparing the world for Transformative AI. Our team works fully in-person in our San Francisco office near Embarcadero station. We love what we do and care about our work a lot.

We strive for excellence and craftsmanship and won't stop until we get there. When the team wins, we all win, and we enjoy collaborating and inspiring each other to grow as a team and as individuals.

We also value emotional honesty, kindness, and bringing your whole self to work. We build machines; we don't try to be machines.

We want you to be able to do the most impactful work of your career at TypeSafe and help define our future as a company.

We provide

- Base salary of $180k-280k plus equity, based on leveling

- 100% covered health insurance

- Daily lunch and dinner

- Visa sponsorships

- 401K plans

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