ML Research Scientist

About the role

Ask the questions whose answers change what the platform does. The work is empirical and runs on our own hardware, measuring real model behavior when sharing silicon and turning insights into product decisions.

Key responsibilities

• Design and run experiments on real fleets rather than synthetic proxies.
• Investigate model behavior under co‑location, quantisation, adapter serving and mixed‑precision execution.
• Translate findings into actionable decisions for the orchestration layer and collaborate with engineering to implement them.
• Publish internal results with the same rigor as external research, including methods, data and limitations.
• Maintain honesty about what results support and what they do not.
• Track literature to distinguish proven findings from claims.

Required profile

• Doctorate or equivalent research experience in machine learning, systems, or a numerate discipline.
• End‑to‑end experiment experience, including instrumentation.
• Strong Python skills and comfort reading/modifying model and serving code.
• Discipline to state limitations before they are discovered by others.
• Published work in efficiency, quantisation, serving or systems for machine learning (optional).
• Experience with adapter methods, distillation or mixture‑of‑experts serving.
• A track record of research that has shipped.

Required skills

• Python
• Model serving code
• Quantisation
• Mixed‑precision execution
• Adapter methods
• Distillation
• Mixture‑of‑experts
• Hardware co‑location

What we offer

• One of the first deep‑tech companies in the region, building foundational technology in‑house.
• Meaningful ownership and impact at an early stage.
• Competitive early‑stage compensation.
• Close collaboration with a small, senior team.
• Problems that combine hardware, systems and AI at scale.