logcat.ai is a VC-backed startup building applied AI systems for Linux and Android devices to help diagnose and remediate OS stack issues. The role focuses on applied ML systems engineering rather than foundational model research.

Company: logcat.ai

Role: Member of Technical Staff, Applied AI

Location: Remote (4h overlap with Pacific or IST; Seattle or Bengaluru on-site preferred)

Experience:

10+ years of relevant engineering experience
Production ML systems experience end to end: data pipelines, fine-tuning, eval, deployment

Key Skills:

Applied ML systems
Fine-tuning and distillation with open-weight models (Qwen, Llama-class)
Eval harness design for correctness-sensitive tasks
Inference deployment and scaling (vLLM or equivalent)
CLI-based AI coding tools like Claude Code

Responsibilities:

Instrument product to convert investigations into structured training data
Build eval harness for diagnostic accuracy and root-cause correctness measurement
Distill deep-investigation runs into small, fine-tuned models maintaining quality at lower cost
Deploy inference including on-prem and airgapped SLMs for secure customer environments

Additional responsibilities:

Work directly with founders in a small, senior team
Focus on applied ML systems rather than foundational model training or research

Nice to have:

Experience with 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 infrastructure background

Other:

VC-backed startup environment
Full-time position
Candidates should describe ownership and hardest shipped project in application

Member of Technical Staff, Applied AI

Skills Required

Description