Machine Learning Manager, London

Join to apply for the Machine Learning Manager, London role at myGwork - LGBTQ+ Business Community.

This job advert is with Isomorphic Labs, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming, enabled by machine learning, with a focus on accelerating drug discovery. The company fosters an interdisciplinary team with a collaborative culture.

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. The team develops predictive and generative AI models to accelerate scientific discovery and drug design across multiple therapeutic areas and modalities.

Machine Learning Engineering Lead, London — You will play a pivotal role in shaping and driving the engineering foundations that underpin an AI-first approach to drug discovery. You will lead a team of ML and full stack software engineers, guiding them in building robust, scalable, and innovative machine learning systems and infrastructure. Your work will translate groundbreaking research into tangible tools and platforms that accelerate medicine discovery. This is an opportunity to combine passion for machine learning, software engineering excellence, and leadership to impact human health.

• Technical Leadership & Vision: Provide technical direction for a team of ML, Fullstack and Backend Software Engineers. Define and drive the technical roadmap for ML systems, infrastructure, and tooling in collaboration with research scientists, ML researchers, and other engineering teams.
• Team Mentorship & Development: Mentor and grow teams of ML SWEs, Fullstack and Backend SWEs, fostering technical excellence, innovation, and collaboration. Guide on career development, best practices, and problem-solving.
• ML System Design & Implementation: Lead design, development, deployment, and maintenance of scalable, production-ready ML models, pipelines, and platforms, including data ingestion, preprocessing, model training, evaluation, serving, and monitoring.
• Software Engineering Excellence: Champion best practices in software engineering, including code quality, testing, CI/CD, version control, documentation, and infrastructure as code. Ensure high-quality, maintainable, and efficient software.
• Cross-Functional Collaboration: Work with AI researchers, biologists, chemists, and engineers to translate research ideas into production systems and apply ML to complex scientific challenges.
• Innovation & Problem Solving: Stay at the forefront of ML, MLOps, and software engineering. Evaluate new technologies to enhance capabilities for drug discovery.
• Project Management & Execution: Oversee complex ML engineering projects, ensuring timely delivery and alignment with goals. Manage priorities, resources, and timelines.
• Operational Excellence: Ensure reliability, scalability, and efficiency of ML systems in production. Implement monitoring, alerting, and incident response processes.

Essential:

• Demonstrable experience in an ML engineering leadership or management role, including mentoring and guiding engineering teams.
• Proven software engineering experience with a strong focus on machine learning.
• Strong proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, JAX, scikit-learn).
• Solid understanding of ML concepts, algorithms, and best practices (deep learning, reinforcement learning, generative models, MLOps).
• Experience designing, building, deploying scalable ML systems in production (cloud platforms such as GCP, AWS, or Azure).
• Excellent software engineering fundamentals (data structures, algorithms, design patterns, distributed systems).
• Experience with MLOps tools (e.g., Kubeflow, MLflow, Airflow) and ML-focused CI/CD.
• Strong communication, collaboration, and problem-solving skills.
• Ability to thrive in a fast-paced, interdisciplinary research environment.
• MSc or PhD in Computer Science, ML, AI, or related field, or equivalent practical experience.

Preferred Qualifications:

• Experience in scientific research environments, particularly in drug discovery, bioinformatics, cheminformatics, or computational biology.
• Familiarity with large-scale data processing frameworks (e.g., Apache Spark, Beam).
• Experience with containers (e.g., Docker, Kubernetes).
• Contributions to open-source ML projects.
• -track record of leading impactful ML projects from conception to deployment.
• Experience working with very large datasets.

We are guided by shared values: Thoughtful, Brave, Determined, Together, and Creating An Extraordinary Company. We are committed to equal employment opportunities and welcome applicants with diverse backgrounds. If you have a disability or need accommodation, please let us know.

Hybrid working: We follow a hybrid model and would require you to be able to come into the office 3 days a week (Tuesday, Wednesday, and one other day depending on team). We are open to discussing additional needs during screening.

Privacy: When you submit an application, your data will be processed in line with our privacy policy.

We are not including extra roles or outdated listings in this description.

Note: This job description remains focused on responsibilities and qualifications for the role and adheres to the job posting’s content.