ML engineering services
We design, build, and ship production ML systems.
ML infrastructure, optimized inference, applied research, and LLM training and fine-tuning, delivered end-to-end by a research-grade engineering practice.
Founded by an ML researcher: NeurIPS · ICML · University of Oxford · École Polytechnique.
What we do
Four service areas, end-to-end.
Each engagement maps to one of the four capabilities below. Every project is led by an engineer with research depth and production scars.
ML infrastructure & platform engineering
Distributed training and serving infrastructure that scales with the work, not the team running it.
Optimized inference & deployment
Cut latency, cost, or both. Production serving stacks designed for the scale and reliability your users see.
Applied research & R&D
Targeted research that ends in shippable code, not slide decks. Built on a research foundation that knows the difference.
LLM training & fine-tuning
Domain-specific language models, end-to-end. From data and eval design through SFT, preference optimization, and deployment.
Why Snapshard
Three things you can count on.
Research-grade rigor
Decisions are grounded in benchmarks, ablations, and the literature. We say what we know and what we are guessing.
End-to-end ownership
One technical lead from scoping through ship. No handoff seams between strategy, modeling, and infrastructure.
Built for production
Latency, cost, reliability, and observability are first-class constraints, not refactors after the demo lands.
Have an ML system to ship?
Tell us what you're building. A 30-minute call is enough to know if we're a fit.