Machine Learning Engineer

Visia is hiring a Machine Learning Engineer to improve the vision agent that trains, evaluates, and iterates on models used in industrial vision systems. The role focuses on post-training open-weight models, building the agent harness and tools, and evaluating answer quality and cost before deployment.

Responsibilities:

• Post-train open-weight models on our own tasks: SFT on curated traces, then RL with verifiable rewards (GRPO and its variants, and DPO-style preference methods where they fit). Build the reward functions, the rollout environment, and the eval gate, then serve the result
• Own the agent harness: context management over long multi-turn sessions, tool-call budgets, background tools, failure recovery, and the policy that decides which tool calls need approval
• Grow the tool catalog (SQL over Postgres and ClickHouse, frame retrieval, segmentation, depth, model training and evaluation), and give each tool a typed schema, clear errors, and a test
• Run the evaluation loop: replay real questions against a candidate harness or model, grade the answers with calibrated judges, and report quality and dollars per correct answer before anything ships
• Push open-source models beyond their weight class with routing, test-time selection, and advisor and planner/worker setups in which a strong model plans and cheap ones execute