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# MLOps Engineer - Implementation

- **Company:** BMW AG
- **Location:** München, Germany
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, AUTomotive Open System Architecture (AUTOSAR), Relational Databases, Software Debugging, Distributed Computing Environment, Python (Programming Language), PostgreSQL, Data Ingestion, Kubernetes Helm Charts, Kubernetes, Information Technology, Build Tools, Machine Learning Operations, Terraform, Data Pipelines
- **Published:** June 2, 2026
- **Apply:** https://www.jobfinder.de/job/mlops-engineer-implementation-f-m-x/

## About the Role

- University degree in Computer Science, Engineering, or a related field. 
- 3-5 years of hands-on ML infrastructure or MLOps experience. 
- Strong Python skills; experience with hermetic build systems (e.g., Bazel) is a plus. 
- Production Kubernetes experience, including deploying and debugging workloads, writing Helm charts, and managing accelerator node pools. 
- Working knowledge of ML pipeline orchestration, experiment tracking, and hyperparameter optimization. 
- Hands-on experience with infrastructure-as-code for AWS (e.g., Terraform) and automotive measurement data, such as MDF4 or MCAP. 
- Comfortable with relational databases (e.g., PostgreSQL) for metadata stores and experience with dataset management tools, functional-safety awareness (ISO 26262), or AUTOSAR Adaptive. 

 

**Wir bieten**

 
- Challenging projects with which we shape the mobility of tomorrow together. 
- Wide range of



## Description

orchestration tools: from data ingestion to distributed training, evaluation, model compilation, and deployment-ready artefacts.

- Furthermore, you engineer petabyte-scale data pipelines that consume domain datasets, transforming raw MDF4 (.mf4) and MCAP log files into training-ready formats. 
 - You build tooling for efficient parallel readers, signal extraction, synchronisation of multi-sensor streams, and integration with dataset management platforms for visual QA and curation. 
 - Also, you manage experiment tracking, hyperparameter tuning and model registry, enforcing reproducibility, lineage, and approval gates from experiment to production. 
 - You develop and maintain model compilation and optimisation pipelines targeting in-vehicle Qualcomm Snapdragon Ride chips and/or NVIDIA automotive SoCs. 
 - On top, you operate observability stacks, providing dashboards, data-drift alerts, pipeline SLOs, and log aggregation. 

**Profil**




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