Senior Applied AI / ML Data Engineer

• 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 remuneration.
• High level of job security.
• Annual special payments such 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

Do you have experience in Python?, * 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? Apply now!

Pulled from the full job description

• Flexible schedule

Artificial Intelligence and machine learning are at the cutting edge when it comes to shaping next-gen mobility in areas like automated driving. But it takes real intellectual leadership and expertise to identify and then harness the AI trends and technologies that will transform the way people travel for good.

We are an international team of experts shaping the future of intelligent mobility by developing privacy-first data and model solutions for BMW’s next-generation edge AI products. Together, we enable fast iteration and innovation for the BMW Intelligent Personal Assistant.

What awaits you?

• You design data pipelines for ingestion, curation, pseudonymization, and versioning.
• Furthermore, 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 such as latency, memory, hallucination, safety, and harms.
• You optimize dataset construction for small LLMs, including instruction tuning, preference data, and synthetic data with controls.
• You build and operate the data pipelines and provide self-serve tools for the team.