Labelbox jobs, judged for you, free

What they do

Labelbox makes training data, RL environments, and evaluations that AI labs use to train agents. An RL environment is a sandbox where an AI agent practices tasks. Its Alignerr service uses expert annotators, and its Recursion platform runs fleets of agents for enterprises. Labelbox started in 2018, raised $189M, and says it is profitable.

What they value

• Make customers win.
• Seek to understand: go to the source and ask first.
• Craftsmanship: do a few things remarkably well.
• Impact over process, like an early-stage startup.
• High agency, ownership, and fast decisions.
• Continuous learning.

Where they hire

Of 10 Postings, eight are in the San Francisco Bay Area. One finance role is remote in India. A contract recruiter role is remote and open to recruiters in Latin America, Europe, and other regions. The headquarters is in the Mission District of San Francisco. The Postings say nothing about visa sponsorship.

Teams and roles

Five of the 10 roles sit in Alignerr Services, the group that makes human data for AI labs.

• A forward deployed engineer, who works directly with customers, and a member of technical staff build sandboxed RL environments: terminals, browsers, and tool workspaces where agents train.
• A forward deployed research scientist fine-tunes open-weight models to test whether client data works. The team has five people.
• A forward deployed engineering manager leads the engineers who scope customer data programs.
• A managing partner and a frontier data lead run delivery and growth for client programs.
• Engineering: a staff ML engineer builds environments, verifiers, and fine-tuning pipelines.
• Also on the board: a contract recruiter for domain experts, a contract recruiting operations role, and an accounts receivable analyst.

What they look for

Engineering roles ask for strong Python, and the environment roles also ask for Go, Rust, or C++. They ask for Docker and sandboxing, and working knowledge of reinforcement learning. The environment roles ask for 2+ years and the staff role for 3+ years with SFT and RL fine-tuning. The research role asks for an MS or PhD and LLM fine-tuning. Postings ask for speed, from spec to working system in days. The eight Bay Area Postings give a base salary range.