Head of ML Engineering - Generative Biology Institute

The Ellison Institute of Technology (EIT) Oxford tackles humanity’s greatest challenges by turning science and technology into impactful global solutions. Focused on areas like health, food security, sustainable agriculture, climate change, clean energy, and AI-driven government innovation, EIT Oxford blends groundbreaking research with practical applications to deliver lasting results.

A cornerstone of EIT Oxford’s mission is its upcoming 300,000-square-foot research facility at the Oxford Science Park, set to open in 2027. This cutting-edge campus will feature advanced labs, an oncology and preventative care clinic, and collaborative spaces to strengthen its partnership with the University of Oxford. It will also host the Ellison Scholars, driving innovation for societal benefit.

The Generative Biology Institute (GBI) at the Ellison Institute of Technology (EIT) Oxford aims to overcome two major challenges in making biology engineerable: 1) the ability to precisely synthesize entire genomes, and 2) understanding which DNA sequences will create biological systems that perform desired functions. Solving these challenges will unlock the potential of biology for transformative solutions in health, sustainability, agriculture, and more. GBI will house 30 groups and over 300 researchers, supported by cutting-edge facilities and sustained funding to address global challenges and advance biology engineering.

EIT Oxford fosters a culture of collaboration, innovation, and resilience, valuing diverse expertise to drive sustainable solutions to humanity’s enduring challenges.

GBI is seeking a Head of ML Engineering to drive its AI/ML strategy, infrastructure, and innovation in synthetic biology. In this pivotal role, you’ll oversee the development and deployment of cutting-edge AI solutions to accelerate research, working in close collaboration with the EIT AI team and internal scientific partners. You’ll lead a cross-functional team of ML engineers and data scientists, design scalable AI systems, and ensure seamless integration with GBI’s broader scientific computing ecosystem.

Requirements

Key Responsibilities:

• To lead and manage the GBI’s AI infrastructure, ensuring scalable, high-performance environments for training, deploying, and monitoring machine learning models.
• To collaborate closely with the EIT AI team including to align GBI AI infrastructure with the EIT AI ML team, and to identify opportunities for AI to transform scientific discovery, lab automation, and operational efficiency.
• To develop and implement a strategy for AI enablement at GBI to support scientific research in synthetic biology; collaborating with research teams and platform leads to design AI/ML models that accelerate and optimise experiments.
• To recruit, lead, and mentor a cross-functional team of ML engineers, data scientists, and AI platform developers, fostering a culture of innovation and responsible AI practice.
• To deploy and maintain robust infrastructure for AI development, including GPUs, model versioning, reproducibility frameworks, and model deployment pipelines.
• To identify, integrate, and manage tools and frameworks for deep learning, generative models, reinforcement learning, and other advanced techniques relevant to synthetic biology and chemistry.
• To work closely with the Head of Scientific Computing and Head of Bioinformatics, ensuring seamless integration of AI pipelines with data systems, high-performance compute infrastructure, and experimental workflows.
• To ensure ethical and regulatory compliance in AI use, including data privacy, model interpretability, and reproducibility.

Essential Knowledge, Skills and Experience:

• A PhD (or equivalent experience) in machine learning, computational biology, AI, or a related field, with a strong track record applying AI to scientific problems.
• Extensive experience building and scaling AI/ML systems, ideally in a research, biotechnology, or tech-forward lab environment.
• Deep technical expertise in:
• Developing pipelines for efficiently training machine learning models
• Creating databases and setting up analytics to track training runs
• Cloud computing platforms, as well as HPC environments.
• Experience working in close collaboration with scientists, with the ability to translate biological or chemical questions into ML problems.
• Strong leadership skills, with a proven ability to lead teams at the intersection of data science, software engineering, and research.
• Exceptional communication skills, with the ability to articulate AI strategies and explain model outputs to both technical and non-technical audiences.

Benefits

We offer the following salary and benefits:

• Salary:  Competitive salary on offer
• Enhanced holiday pay
• Pension
• Life Assurance
• Income Protection
• Private Medical Insurance
• Hospital Cash Plan
• Therapy Services
• Perk Box
• Electrical Car Scheme

Why work for EIT:

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!

Terms of Appointment:

You must have the right to work permanently in the UK with a willingness to travel as necessary.

You will live in, or within easy commuting distance of, Oxford.

Flexibility to be discussed.

During peak periods, some longer hours may be required and some working across multiple time zones due to the global nature of the programme.