Member of Technical Staff, Model Capabilities
About this role
The Home organization is seeking a Member of Technical Staff, Model Capabilities to join its team based at the San Francisco Office. This full-time position suits generalist engineers who want to build data-tooling interfaces and advance model intelligence.
Role Overview
This position involves advancing model intelligence through the creation of interfaces, datasets, and evaluation tooling. The team values individuals who combine product sense, data science, and engineering to ensure production-ready reliability in real-world applications. Team members work fully in person from the San Francisco office near Embarcadero station.
Key Responsibilities
Requirements
Skills and Tools
Salary and Benefits
About the Company
Home operates as an AI lab building machine-native intelligence infrastructure for automation. The group combines the intelligence of LLMs with the efficiency and reliability of code into System One Models. Founded by alumni from OpenAI, Google Brain, and Meta/FAIR, the enterprise is backed by top-tier investors and focuses on real-world reliability and autonomy in production.
How to Apply
Candidates should apply directly on the official company careers page.
Skills and tech stack
Questions candidates ask
What is the location of the Member of Technical Staff role?
The position is fully in person at the San Francisco office near Embarcadero station.
What salary and benefits are offered for this position?
The base salary ranges from $150,000 to $250,000 per year plus equity, based on leveling. Benefits include 100% covered health insurance, daily lunch and dinner, visa sponsorships, and 401K plans.
What technologies are used in the tech stack?
The primary tech stack uses Python, TypeScript, Next.js, Tailwind CSS, and Kubernetes for orchestration.
What are the primary responsibilities of the role?
Responsibilities include building internal data-tooling and evaluation interfaces, creating high-leverage datasets, developing evaluation frameworks, running rigorous experiments, and partnering with product managers.
Who is an ideal candidate for this job?
An ideal candidate is a generalist with solid fundamentals, strong coding abilities, product intuition, hands-on LLM implementation experience, and the ability to thrive in ambiguous problem spaces.