You will lead a team working to build, scale, and optimize the machine learning infrastructure that powers Recursion’s drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on‑prem and in the cloud. You will work cross‑functionally across ML engineering, data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions.
In This Role You Will:
- Enable AI/ML, LLM, and Agentic Systems teams for scale – build and operate platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion’s massive datasets and deep learning workloads.
- Act as a mentor, coach, and sponsor – share technical, leadership and managerial skills in MLOps, distributed computing, and infrastructure engineering to drive impact, learning, and growth across teams.
- Enable a model‑driven culture – work with stakeholders to ensure our ML infrastructure supports rapid experimentation, reliable model deployment, and continuous improvement.
The Team You’ll Join:
You’ll be part of a group of technical leaders who collaborate on engineering leadership, ML system architecture, MLOps patterns, and infrastructure optimization. The team tackles model scalability, deployment reliability, and infrastructure efficiency across the company.
The Experience You Will Need:
- Hands‑on tech lead or manager experience focused on infrastructure, MLOps and distributed systems, with deep technical engagement on ML, orchestration and agentic systems.
- A people‑first mindset that prioritizes coworker growth and experience and understands Conway’s Law.
- Demonstrated record of learning from and teaching peers in ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps architecture.
- Willingness to learn new parts of the ML tech stack – Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and model serving frameworks.
- Fluency in life sciences or drug discovery is a plus.
Working Location & Compensation:
This is an office‑based, hybrid position at our London, England office. Employees are expected to work in the office at least 50% of the time.
Estimated annual base range: £96,052 to £127,237. Eligible for annual bonus, equity, and a comprehensive benefits package.
The Values We Hope You Share:
- Act boldly with integrity – take calculated risks while respecting ethics, science, and trust.
- Care deeply and engage directly – hold responsibility, respect, honesty, and action.
- Learn actively and adapt rapidly – experiment, test, refine, and embrace iteration.
- Move with urgency because patients are waiting – speed with purpose.
- Take ownership and accountability – enable trust and autonomy.
- We are One Recursion – cross‑functional collaboration built on trust, clarity, humility, and impact.
Equal Opportunity Employer
Recursion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation.
Accommodations
Accommodations are available on request for candidates taking part in all aspects of the selection process.
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