R&D Machine Learning Engineer

About the role

DeepLab is an AI and machine learning company combining software technology with research in machine learning and deep learning. It is expanding its R&D teams and is looking for an accomplished ML engineer with a strong engineering foundation, proven research output and hands-on development experience. The role focuses on EU-funded R&D projects (e.g. Horizon Europe), with ownership of technical deliverables from experimental design through implementation and reporting, and also involves preparing research and innovation proposals.

Key responsibilities

• Design, develop and implement machine learning and deep learning algorithms in funded EU R&D projects, owning technical workstreams and deliverables.
• Conduct literature surveys, experimentation and benchmarking, and develop proof-of-concept systems and prototypes.
• Prototype and evaluate LLM-based and agentic systems such as retrieval-augmented generation pipelines and tool-using agents.
• Perform statistical modeling, model development and evaluation, data analytics and dataset management, and optimize models and pipelines for scalability, efficiency and reproducibility.
• Contribute to project milestones, technical reports and the writing of technical content for EU grant proposals and industrial R&D calls.
• Collaborate with ML engineers, domain experts and software developers, share knowledge and mentor junior colleagues.

Required profile

• MSc in Electrical & Computer Engineering, Computer Science, Machine Learning, Applied Mathematics, Statistics, Physics, Signal Processing or a closely related quantitative field; a PhD is a plus but not required.
• 4+ years of hands-on ML experience, with evidence of owning technical workstreams end-to-end.
• Demonstrated application experience in at least one major ML domain (computer vision, NLP, signal/audio processing, time-series analysis or LLM-based/generative AI).
• Strong foundations in core ML, including deep learning architectures, optimization, probabilistic modeling and statistics.
• Experience with technical and scientific writing, and comfort with Linux, Git, CI/CD, Docker and collaborative development.

Required skills

• Proficiency in Python and fluency in PyTorch, JAX or TensorFlow.
• Experiment tracking (MLflow, W&B or equivalent), version-controlled and tested code, reproducible pipelines and CI workflows.
• Model deployment experience is a plus.

What we offer

• Supplementary private health insurance.
• Flexible working hours and remote work opportunities.
• Budget for home office equipment and productivity, and a personal development budget.
• Knowledge-sharing sessions and a newly designed office environment.
• Competitive salary based on experience and qualifications.