Data Demons

TypeSafe AI
San Francisco Office, US
On-site

Who this role is best for

Aimed at mid-to-senior level engineers who build data and evaluation tooling, with a focus on production-ready AI and cross-functional collaboration.

Best fit for

  • Candidates with Python expertise and a passion for building production-ready AI systems
    — “Our tech stack is primarily Python”
  • Engineers who bridge data science and product development through creative, real-world solutions
    — “combining product sense, data science, and engineering”

Things to consider

  • In-person work is required at the San Francisco office
    — “We work fully in person from our San Francisco office”
  • The role demands high attention to detail and a strong bar for quality
    — “Maintain high attention to detail and a strong bar for quality”

How to stand out

  • Highlight end-to-end ownership of data and evaluation tools in your resume and interviews
    — “owning a domain end-to-end, with craft and judgment over simple optimization”
  • Showcase experience with LLMs, including their limitations and real-world applications
    — “Have hands-on experience implementing LLMs and understand their capabilities and limitations”
  • Emphasize your ability to translate real-world needs into system improvements
    — “Partner closely with product managers and customers to translate real-world needs into concrete model and system improvements”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed high-leverage datasets and products
  • Built internal data-tooling and evaluation interfaces
  • Developed evaluation frameworks for model quality
Typical background
Experience in data science and engineeringStrong coding skills

Skills & requirements

Required

PythonData ScienceMachine LearningData EngineeringProduct SenseAttention To DetailProblem Solving

Preferred

LLM ImplementationKubernetesTypeScriptNext.jsTailwind CSS

Stack & domain

PythonTypeScriptNext.jsTailwind CSSKubernetesProduct SenseData ScienceEngineeringAttention To DetailQualityTeamworkProblem-solvingCreativityLeadershipAILlmsData-toolingEvaluationModel DevelopmentReliabilityTrustworthy AI

About the role

Original posting from TypeSafe AI via Ashby

ABOUT TYPESAFE

We’re building prod, not god. TypeSafe is an AI lab pushing frontier model intelligence in a new direction, starting with System One Models. We combine the reasoning of LLMs with the reliability of code, for truly trustworthy AI. Our first model, Jev, launched in September 2026.

While others chase leaderboards, we’re rebuilding the LLM stack from first principles to make models smarter and also dependable enough to run in production. We’re a small, fast team backed by an $870M Series A led by a16z. Made in SF, with love. Come join the frontier.

ABOUT THE ROLE

We're looking for scrappy engineers who ship data-tooling interfaces fast. You will progress model intelligence through the interfaces, datasets, and evaluation tooling you build, combining product sense, data science, and engineering. You'll be part of the real "secret sauce" of TypeSafe: figuring out how our models can provide production-ready reliability in the real world.

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 AI and agents.

WHAT YOU'LL DO

Check out our team video: https://vimeo.com/1231083924/22b52f6b1d

  • Create high-leverage datasets, products, and user interfaces that unlock new capabilities and use cases on top of our model
  • Build internal data-tooling and evaluation interfaces — fast — that make model development clearer (evaluation, debugging, data inspection)
  • Develop and own evaluation frameworks to measure quality, reliability, and emergent characteristics across model iterations
  • Run rigorous analyses and experiments to understand how data, training choices, and targeted interventions impact model behavior
  • Turn raw model outputs and data into clear, inspectable UIs — owning a domain end-to-end, with craft and judgment over simple optimization
  • Partner closely with product managers and customers to translate real-world needs into concrete model and system improvements
  • Continuously iterate, learn, and co-discover new techniques for building exceptional, trustworthy AI products

WE ARE LOOKING FOR PEOPLE WHO

  • Are generalists with solid fundamentals, strong coding ability, and product intuition
  • Maintain high attention to detail and a strong bar for quality
  • Enjoy thinking beyond the code to how systems are used in the real world
  • Are scrappy and hacky, and thrive in ambiguous problem spaces — taking satisfaction in finding creative solutions
  • Don't trust LLMs blindly — they look at the reality of model generations
  • Have hands-on experience implementing LLMs and understand their capabilities and limitations

LIFE AT TYPESAFE

We’re a small, flat, close-knit team working to make intelligence dependable enough to become part of everyday software. We work fully in person from our San Francisco office near Embarcadero station. We love what we do and care deeply about the work.

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

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

WE PROVIDE

  • 100% covered health insurance
  • Daily lunch and dinner
  • Visa sponsorships
  • 401K plans

Source: TypeSafe AI careers (Ashby)

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