Head of Platform Engineering

Core responsibilities:

• Own the end-to-end platform and infrastructure strategy supporting data, training, and large-scale inference.
• Design and operate systems for large-scale AI workloads, with strong judgment around build vs. buy decisions.
• Navigate infrastructure complexity across the full lifecycle: data ingestion and storage, distributed training, evaluation, and production inference.
• Build, lead, and mentor a high-impact platform engineering team.

This role enables the next generation of AI-driven drug discovery, applying large-scale AI to create real-world scientific impact and work on AI that is genuinely good for humanity.

Required skills and experience:

• Proven experience designing and operating infrastructure for AI training and inference at scale.
• Strong systems thinking and the ability to reason about tradeoffs across performance, cost, reliability, and velocity.
• Experience leading teams in fast-moving environments, with a startup mindset.
• Comfort operating across abstraction layers, from cloud and hardware to ML platforms and developer tooling.

No specific benefits, compensation, or perks mentioned in the job description.

Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. The company's generative and predictive AI platform, GEMS, integrates AI and physics into industry-leading models to generate and optimize drug molecules.