Join TypeSafe AI as an engineer to build data-tooling interfaces that enhance model intelligence in a fast-paced startup environment.
Posted by employer 5 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
Must have
Nice to have
AI in the day-to-day
We empower developers to use any tooling they find helpful for getting their job done, including AI and agents.
Requirements
Not disclosed in this posting: compensation, seniority, years of experience.
Benefits
Joblaze summary
In this role, engineers at TypeSafe AI focus on developing data-tooling interfaces that enhance model intelligence and ensure production reliability. The position requires proficiency in Python, along with familiarity in TypeScript, Next.js, and Kubernetes, as well as a strong understanding of LLMs. Ideal candidates are generalists with solid coding skills and a knack for translating real-world needs into effective model improvements. TypeSafe fosters a collaborative environment, emphasizing craftsmanship and emotional honesty within a small, dedicated team.
Joblaze insights
Quick facts
From the original posting
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.
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
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
100% covered health insurance
Daily lunch and dinner
Visa sponsorships
401K plans
Standard company text repeated across TypeSafe AI's postings is omitted here.