Machine Learning Manager, London

Isomorphic Labs Limited; City of London; Hybrid; GBP 85,000 - 110,000; Full time

Job summary

A pioneering AI-driven company in London seeks a Machine Learning Manager to lead a team of engineers in creating innovative solutions for drug discovery. This role offers the opportunity to shape technical direction and drive impactful projects. Ideal candidates will have significant experience in ML engineering, strong skills in Python and machine learning frameworks, and a relevant master's or doctorate degree. The position supports a hybrid work model, fostering collaboration and innovation.

Benefits

Hybrid work model

Opportunities for mentoring

Collaborative culture

Qualifications

• Demonstrable experience in ML engineering leadership.
• Proven experience in software engineering focusing on machine learning.
• Experience designing scalable ML systems in production.

Responsibilities

• Lead a team in building scalable, innovative ML systems.
• Provide technical direction and mentorship to engineering teams.
• Drive the technical roadmap for ML systems and infrastructure.

Skills

Python

Machine Learning frameworks

MLOps tools

Strong communication skills

Software engineering fundamentals

Education

MSc or PhD in CS/ML/AI or related field

Tools

TensorFlow

PyTorch

Kubeflow

Docker

Job description

Join to apply for the Machine Learning Manager, London role at Isomorphic Labs.

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, to accelerate drug discovery. We are an interdisciplinary team driving groundbreaking innovation with a collaborative culture. We are building a world where AI helps design novel molecules, anticipate drug performance, and develop medicines to treat and cure diseases. We have built a world-leading drug design engine and are innovating on model architecture to advance rational drug design. Our mission is to one day solve all disease with the help of AI.

Machine Learning Engineering Lead, London

Your Impact
As a Machine Learning Software Engineer Lead at Isomorphic Labs, you will shape and drive the engineering foundations that underpin our 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 the discovery of new medicines. This is a unique opportunity to combine machine learning, software engineering excellence, and leadership to impact human health.

Key Responsibilities:

• 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 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 and best practices.
• ML System Design & Implementation: Lead design, deployment, and maintenance of scalable, production-ready ML models, pipelines, and platforms, including data ingestion, preprocessing, training, evaluation, serving, and monitoring.
• Software Engineering Excellence: Champion software engineering best practices, including code quality, testing, CI/CD, version control, documentation, and infrastructure as code. Ensure high-quality, maintainable software.
• Cross-Functional Collaboration: Work with AI researchers, biologists, chemists, and other engineers to translate research ideas into production systems and apply ML to scientific challenges.
• Innovation & Problem Solving: Stay at the forefront of ML, MLOps, and software engineering; evaluate new technologies to enhance capabilities in 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 with robust monitoring, alerting, and incident response.

Skills And Qualifications

Essential:

• Demonstrable experience in an ML engineering leadership or management role, including mentoring and guiding engineering teams.
• Proven experience in software engineering with a 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 (e.g., deep learning, reinforcement learning, generative models, MLOps).
• Experience designing, building, and 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 CI/CD.
• Strong communication, collaboration, and problem-solving skills; ability to thrive in a fast-paced, interdisciplinary environment.
• MSc or PhD in CS/ML/AI or related field, or equivalent practical experience.

Preferred Qualifications:

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

Culture and values

We are guided by shared values that shape our work: Thoughtful, Brave, Determined, Together, and Creating An Extraordinary Company. We emphasize curiosity, initiative, collaboration, and impact, and are committed to equal employment opportunities regardless of protected characteristics. If you require accommodations due to a disability or additional need, please let us know. We support a hybrid work model and may require in-person collaboration three days per week.

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