Job Title – Machine Learning Engineer Type – Contract Location – Berlin, Germany (Remote) Duration – 12 Months (Extendable) Key job responsibilities Work directly with the science and engineering teams to build systems for provably correct AI reasoning with LLMs Build a system that generates automatically annotated data with an existing reasoning engine (AI planner, simulator, proof planner) Handle large-scale data annotations and automate pre/post-processing pipelines, including data lake management in S3 and compute resources.
Build pipelines for training and fine-tuning LLMs with data Build an experimental test harness able to run experiments in multiple domains with the minimum of adaptation. Take part in scrum development in an international setting (Berlin, Boston, and Seattle) Basic qualifications 3+ years of experience with training/deploying deep learning/ML models (3+ years) Strong knowledge of relevant ML tools (PyTorch, HuggingFace, SageMaker, vLLM ) Experience in scripting for automation (e.g.
Python) Experience using Cloud Storage and Computing technologies (AWS, EC2, S3, SageMaker, Lambda) Capacity to independently lead and execute end-to-end insight projects, including asking the right questions, managing complex datasets, iterating on findings, and providing strategic guidance and recommendations to an engineering team Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relations Preferred Qualifications Master’s degree in computer science Experience with Reinforcement Learning and/or transformer-based models Experience with theory and practice of design of experiments and statistical analysis of results Experience programming to extract, transform, and clean large (multi-TB) data sets Preferably located in or open to moving to Berlin