Join our machine learning group as a Research Engineer and help drive the development, deployment, and scaling of ML and computational systems across the company. You’ll work at the intersection of research and engineering—improving research workflows, supporting rapid experimentation, and enabling teams to push the limits of modern ML. You’ll collaborate with machine learning scientists, data scientists, platform engineers, and other domain experts across the organisation. Depending on priorities, you may work within a specific ML team or operate in a cross-functional capacity. Based at our wet/dry lab and headquarters in central London, you’ll tackle challenges involving large datasets, complex models, and high-performance compute. Your work will strengthen our training and inference pipelines, improve our software foundations, and optimise our hybrid on-prem/cloud environment, which includes dedicated DGX clusters and collaboration with partners like NVIDIA. This role offers a chance to shape the systems and tools that power cutting-edge ML research. ## Day to day, you will
Work with interdisciplinary teams to solve challenges across data engineering, ML engineering, and software engineering. - Build and improve data processing, transformation, and loading systems to support model training and inference at scale. - Develop and maintain high-quality research and production codebases to enable rapid, reproducible experimentation. - Advance our software engineering practices by optimising systems, streamlining pipelines, and improving robustness across workflows. ##
Professionally, you will have
BSc/MSc/PhD in CS/ML/Engineering (or related), 2+ years industry experience. - Solid understanding of algorithms, data structures, complexity. - Proficiency in Python with clean, maintainable coding practices. - Familiarity with PyTorch and common scientific Python libraries. - Solid understanding of ML fundamentals and modern deep learning. - Experience training, evaluating, and iterating on models. - Familiarity with AWS/GCP, Docker, Kubernetes, and CI/CD. - Familiarity with orchestration tools (Airflow/Prefect) and model-serving frameworks. Bonus experience
Exposure to biology/bioinformatics or ML for scientific domains. ## Personally, you
Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams. - Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work. - Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect. - Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams. - Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes. ## Working Style & Culture at Relation
At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! ## Recruitment Agencies
Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. Relation is a committed equal opportunities employer.
