Research Engineer Machine Learning

A leading technology company operating at the intersection of AI and scientific research is looking for a Research Engineer (Machine Learning) to play a central role in advancing its generative modelling and discovery platform. This role offers the opportunity to apply your machine learning and software engineering expertise to help transform cutting-edge research into scalable, reliable systems. You’ll work closely with scientists and engineers to accelerate innovation across a highly technical, mission-driven environment.

About the company

This organisation is developing an AI-driven platform designed to support complex scientific discovery with a focus on sustainability and real-world impact. The team combines expertise across machine learning, biology, chemistry, and engineering, working collaboratively to build tools that enable faster experimentation and high-quality insights. The company operates with a remote-first approach (within UK/EU time zones) and holds regular in-person team meet-ups to support culture and collaboration.

Key responsibilities

• Work closely with research and engineering teams to integrate generative AI and machine learning models into the company’s discovery platform.
• Translate research prototypes into well-structured, maintainable code suitable for production-level workflows.
• Design and maintain infrastructure to support data ingestion, preprocessing, training, inference, and evaluation at scale.
• Optimise distributed training and inference pipelines, including the use of GPUs and cloud or cluster computing environments.
• Implement monitoring, logging, experiment tracking, and reproducibility best practices across ML workflows.
• Partner with scientists and domain experts to accelerate experimentation cycles and improve research productivity.
• Contribute to engineering standards through documentation, code reviews, and shared best practices.

Required experience and skills

• MSc or PhD in Computer Science, Mathematics, Statistics, or a related technical field (or equivalent research/industry experience).
• Experience working in fast-paced research or engineering environments, ideally within smaller or early-stage teams.
• Demonstrated ability to build and maintain machine learning infrastructure for large-scale training, inference, and deployment.
• Experience working with complex research codebases and contributing to or extending open-source frameworks.
• Strong proficiency with PyTorch and wider ML engineering tooling, including Docker, Kubernetes, CI/CD systems, and cloud platforms.
• Solid software engineering fundamentals, including testing, reproducibility, version control, and documentation.
• Excellent communication skills and a proactive, delivery-focused working style.

Nice to have

• Experience with experiment-tracking and model-monitoring frameworks.
• Familiarity with computational chemistry, bioinformatics, or molecular simulation tools (e.g., RDKit, OpenMM).
• Background with infrastructure-as-code, cloud orchestration, or GPU cluster management.

Your recruiter

As a Senior Recruitment Consultant at Aspire Life Sciences, Julien Funes' expertise lies at the nexus of technology and life sciences. He recruits top Machine Learning and data talent for Biotech and life sciences startups across Europe and North America. He is committed to advancing the industry by sourcing and securing top-tier talent for roles in these critical sectors. His approach enables him to effectively match candidates with opportunities where technological innovation meets life science excellence.