Our mission at Xyme is to solve important societal problems by revolutionizing the practice of synthetic chemistry through what we call xymes - AI-generated enzymes that can catalyze any reaction. As an innovative startup based in Oxford and Manchester, UK, we bring together interdisciplinary teams of scientists and engineers to push the boundaries of enzyme design. Our dynamic and collaborative work environment is fuelled by a passion for innovation. We foster a culture of continuous learning and improvement, where every team member can make a lasting impact on our groundbreaking research and real-world applications.
We are seeking an exceptional MLOps Engineer to support the development and optimisation of our machine learning systems. In this role, you will architect and implement scalable MLOps solutions that power our AI-driven enzyme design platform, enabling rapid experimentation and reliable model deployment. As a key member of our engineering team, you'll have the opportunity to shape our technical vision while working at the intersection of cutting-edge ML infrastructure and revolutionary biotechnology.
What you will doDesign, develop, and maintain infrastructure for the full ML model development lifecycle - training, testing, benchmarking, and deployment - while ensuring scalability and efficiency.
Build and maintain ML pipelines that support diverse model architectures and facilitate rapid experimentation.
Implement robust CI/CD pipelines, automated testing frameworks, and monitoring components.
Develop and maintain data pipelines for processing large-scale biological and chemical datasets.
Use your knowledge of MLOps principles and industry best practices to build modular, reusable components that can be used in a self-serve way by research teams.
Collaborate with the platform team to deploy and scale ML pipelines and computational workflows in cloud environments.
Maintain high code quality, optimise performance, and ensure reproducibility through comprehensive testing, thorough documentation, and robust version control practices.
Strong experience with MLOps practices and tools for model versioning, experiment tracking, and deployment.
Deep expertise in Python and modern ML frameworks (PyTorch, JAX, Hugging Face).
Strong background in cloud computing platforms (AWS, GCP), and containerization technologies (docker, k8s).
Experience with distributed computing frameworks and workflow orchestrators for large-scale dataset processing (Ray, flyte).
Proficiency in implementing and maintaining scalable ML infrastructure in production environments.
Background in one or more scientific fields: structural bioinformatics, cheminformatics, AI/ML, computational chemistry, or molecular dynamics.
Experience with high-performance computing environments and parallel processing.
Contributions to open source scientific and/or ML software projects.
Opportunity to work on groundbreaking technology with real-world impact, making significant contributions to synthetic chemistry and enzyme design.
A supportive and collaborative work environment that nurtures creativity and innovation, providing genuine ownership and autonomy.
Continuous learning and development opportunities, including the chance to attend and present at relevant conferences and industry events.
The excitement of being part of a fast-growing startup at the forefront of AI-driven enzyme design.
Top Skills
What We Do
Enzyme design is the next grand challenge. Nature has spent billions of years evolving the enzymes we use today. Now we must design the enzymes of tomorrow.
Fusing generative AI with experiment creates the opportunity to achieve this. Success will change the way we live, making better use of natural inputs and byproducts, reducing energy requirements, delivering life-changing therapies and providing new agro-bio solutions.
