Member of Technical Staff, Applied AI

logcat.ai

5d • Remote

About The Position

Own the engine that turns every investigation into a compounding asset: the more the platform runs, the sharper it gets. This is applied ML systems, not research. If your goal is training foundation models from scratch and publishing, this is not the seat.

Requirements

• 10+ years of relevant engineering experience.
• Production ML systems experience end to end: data pipelines, fine-tuning, eval, deployment.
• Hands-on fine-tuning and distillation with open-weight models (Qwen, Llama-class).
• Eval harness design for correctness-sensitive tasks, including trajectory-level evals for agentic and tool-use systems.
• Inference deployment and scaling (vLLM or equivalent) on managed platforms.
• Proficient in day-to-day work with CLI-based AI coding tools like Claude Code (or an equivalent).

Nice To Haves

• Agent or tool-use systems.
• Preference optimization (DPO/GRPO-style) and structured-output / function-calling fine-tunes.
• On-prem or airgapped model deployment.
• Retrieval over large heterogeneous corpora.
• Systems or infra background.

Responsibilities

• Instrument the product so every investigation, especially human-corrected ones, becomes structured training data.
• Build the eval harness for diagnostic accuracy. Root-cause correctness has to be measured, not eyeballed.
• Distill expensive deep-investigation runs into small, fine-tuned models that hold the quality bar at a fraction of the cost.
• Deploy inference, including on-prem and airgapped SLMs for customers whose logs cannot leave their environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed