Model Capabilities Engineer
Join TypeSafe AI as a Model Capabilities Engineer to build data-tooling interfaces and enhance model intelligence in a fast-paced environment.
Posted by employer 3 months ago
First seen on Joblaze 1 hour ago
Last verified on the company career page 1 hour ago
Skills & Technologies
What you'll build
- Create high-leverage datasets, products, and user interfaces
- Build internal data-tooling and evaluation interfaces
- Develop and own evaluation frameworks
- Run rigorous analyses and experiments
- Turn raw model outputs into clear, inspectable UIs
Must have
- Strong coding ability
- Hands-on experience implementing LLMs
Nice to have
- Enjoy thinking beyond the code
- Scrappy and hacky mindset
- Attention to detail
- Product intuition
Requirements
- Visa
- Sponsorship available
Not disclosed in this posting: compensation, seniority, years of experience.
Benefits
Joblaze summary
In the role of Model Capabilities Engineer at TypeSafe AI, the individual will focus on developing data-tooling interfaces and evaluation frameworks that enhance model intelligence and reliability for production use. Proficiency in Python, along with familiarity in TypeScript, Next.js, and Kubernetes, is essential for success in this position. This role is ideal for generalists with a strong coding background and a knack for problem-solving in ambiguous environments. TypeSafe fosters a collaborative atmosphere within a small team dedicated to creating dependable AI solutions.
Joblaze insights
- Listed today — first seen on Joblaze October 19, 2026. Last confirmed on TypeSafe AI's careers page October 19, 2026.
- Python appears in 44.5% of 1765 comparable ai/ml roles in United States; Tailwind CSS appears in 0.1% of 1765 comparable ai/ml roles in United States.
Quick facts
- Is the Model Capabilities Engineer role remote?
- No — this is an on-site role in San Francisco, United States.
- Where is the role based?
- TypeSafe AI is hiring for this position in San Francisco, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Kubernetes, Next.js, Python, Tailwind CSS, TypeScript.
- Does TypeSafe AI sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- Is this full-time or contract?
- Full-time for this Model Capabilities Engineer role at TypeSafe AI.
From the original posting
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
We provide
100% covered health insurance
Daily lunch and dinner
Visa sponsorships
401K plans
Standard company text repeated across TypeSafe AI's postings is omitted here.