Senior Applied AI / ML Data Engineer (f/m/x)

You design data pipelines for ingestion, curation, pseudonymization, and versioning. Additionally, you implement reproducible training and finetuning builds for GenAI edge device models. You set up experiment tracking and artifact registries for model variants. Additionally, you build evaluation suites covering relevant KPIs search as latency, memory, hallucination, safety, and harms. You optimize dataset construction for small LLMs, instruction including doing, preference data, and synthetic data with controls. You build and provide the data pipelines and self-serve tools for the team.

University degree in Computer Science, Engineering, or a related field. Several years of experience in machine learning engineering with Python (PyTorch) and strong software fundamentals in testing, profiling, and CI/CD. Practical knowledge of evaluation at scale, including golden sets, online metrics, drift detection, and regression testing. Experience with A/B experimentation, basics of causal inference, and privacy-preserving learning patterns. Motivation to embrace customer problems and find innovative solutions using available technologies. You enjoy working on complex problems in an international in-house team of experts. Professional English proficiency; German is a plus. Are you ready to take proactive action with a hands-on mentality, strong problem-solving skills, and excellent cross-functional communication?

Challenging projects with which we are shaping the mobility of tomorrow together. Wide range of personal and professional development opportunities. Attractive, fair and performance-related costs. High level of job security. Annual special payments search as vacation pay, Christmas bonus, and profit sharing. Flexible working hours including 6 weeks annual leave and overtime compensation. Discounted BMW & MINI conditions. Many other benefits at bmw.jobs/benefits Start date:from now on Type of employment: unlimited Working hours:FULLTIME At the BMW Group, we place great importance on equal treatment and equal opportunities. recruit Ouring decisions are based on the personality, experience, and skills of the applicants. Learn more here. .