Job Description
?? Contract Role: Machine Learning Engineer – Biotech & GenomicsLocation: Hybrid (London based)Contract Type: 12–18 months, Outside IR35Start Date: ImmediateRate: Competitive, based on experienceWe’re working with a group of biotech innovators focused on solving some of the most complex challenges in life sciences — from protein folding and genomic analysis to biomedical imaging and drug discovery. These teams are seeking a Machine Learning Engineer with deep technical expertise and a passion for applying AI to real-world biological problems.?? What You’ll Be Working On:
* Designing and deploying ML models for protein structure prediction, genomic pattern recognition, and cell image segmentation
* Collaborating with bioinformaticians, data scientists, and software engineers to build scalable pipelines for research and clinical applications
* Fine-tuning and optimizing models using tools like AlphaFold, RoseTTAFold, BioBERT, and DeepCell
* Integrating ML workflows with platforms such as Benchling, PubMed APIs, and internal R&D systems
* Supporting model validation, performance benchmarking, and regulatory documentation
?? Key Technologies & Tools:
* ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers
* Bio-AI Tools: AlphaFold, RoseTTAFold, BioBERT, DeepCell, Cellpose
* Data Sources: Genomic datasets, microscopy images, biomedical literature
* Cloud & DevOps: AWS/GCP, Docker, Kubernetes, MLflow
* Languages: Python (essential), SQL, Bash
? Ideal Candidate Profile:
* 4+ years of experience in machine learning, with at least 2 years in biotech, healthcare, or life sciences
* Strong understanding of biological data types (e.g., DNA/RNA sequences, protein structures, cell images)
* Experience working with open-source bioinformatics tools and APIs
* Comfortable building end-to-end ML pipelines in cloud environments
* Familiarity with regulatory considerations in clinical or research settings (e.g., HIPAA, GxP)