🏢 Company overview

Unimatch Lab is an AI-driven venture studio based in Silicon Valley.

We build our own AI technology stack and a portfolio of AI-driven assets: consumer AI products, smart devices, local LLM clusters, and foundational layers (memory layer, RAM/VRAM optimization, orchestration, AI software for infrastructure and compute).

This includes R&D on local, distributed, and orbital data centers and distributed computing.

Our goal is to reach a combined asset valuation of $10B+ by 2032 and rank among the world's top 50 AI companies.

We are an OKR-driven company: measurable outcomes, speed, transparency, and ownership.

We hire A-players: autonomous, fast, strong execution, high accountability.

Learn more: Unimatch Lab Career

🎯 Position summary

Senior ML Engineer owns the in-house LLM/VLM lifecycle: datasets, weight training, evaluation, and self-hosted production. The role is weighted toward fine-tuning and serving on our own infrastructure, not prompt assembly, RAG integration, or third-party LLM APIs.

Personal and sensitive data are processed only on-premises. External cloud LLM APIs are not used for workloads that include such data.

You are expected to run the loop end to end, decide what to retrain from production failures or eval gaps, and keep datasets, eval configs, and release criteria documented so the pipeline is not tied to one engineer.

✅ Key responsibilities

Model training and fine-tuning

• Fine-tune LLM and VLM models for product use cases using LoRA/QLoRA, distillation, and related methods through production-ready weights
• Adapt models to domain-specific tasks without relying on prompt-only or RAG-only approaches as the primary delivery path
• Maintain reproducible training configs and document model versions bound to releases

Evaluation and data