Senior Machine Learning Engineer

I am hiring on behalf of a cutting-edge European based DeepTech biotech developing next-generation AI systems to model cellular biology at single-cell resolution. This team builds large-scale foundation models, learns from multi-omics datasets, and develops predictive tools that accelerate scientific discovery and biological design. If you want to work at the intersection of machine learning, computational biology, and frontier AI research—this role is for you. The RoleWe’re looking for a Machine Learning Engineer who can help build and scale advanced ML systems for single-cell datasets and multi-modal omics. You’ll contribute to designing and training foundation models, improving data processing pipelines, and delivering models that support both research and product-grade use cases. What You’ll DoDevelop, train, and optimize ML models using large-scale single-cell and multi-omics datasetsWork with foundation model architectures, including transformers and diffusion-based approachesBuild robust data pipelines and model training workflows using Python, PyTorch, and modern ML toolingCollaborate with computational biologists, data scientists, and research engineers to integrate biological insightsEvaluate model performance, run experiments, and contribute to core ML research directionsHelp scale models for production environments and internal scientific tooling What We’re Looking ForStrong experience with single-cell omics datasets (scRNA-seq, scATAC-seq, multi-omics, etc.)Hands-on expertise with foundation models or large-scale deep learning architecturesProficiency in Python, PyTorch, and modern ML engineering practicesExperience building training pipelines, handling large datasets, and optimizing model performanceAbility to work in a fast-moving, research-driven DeepTech environmentInterest in computational biology or applied biological modelling (formal biology background not required) Nice to HaveExperience with cloud compute environments, distributed training, or workflow orchestrationExposure to generative models, representation learning, or embeddings for biological dataFamiliarity with data integration across omics modalities Following your application, Jay Robins, a specialist AI recruiter will discuss the opportunity with you in detail. He will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available. This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.