<h1> MLOps Engineer - Implementation (f/m/x) </h1> <p> Referenznummer: 26784_182753 </p> <p> Standort: München, BY, DE, 80809 </p> <p> Unternehmen: BMW Group </p> <p> INNOVATION IS IMAGINING WHAT NO ONE ELSE CAN. </p> <p> At the BMW Group, everything begins with passion. It transforms a profession into a vocation. It drives us to continually reinvent mobility and bring innovative ideas to the roads. Enthusiasm for collaborative projects turns a team into a strong unit where every opinion is valued. It is only when expertise, highly professional processes, and enjoyment of work come together that we can shape the future collectively. </p> <p> We build and operate the ML infrastructure that takes perception and vision models from experiment to production - across a data mesh of domain-owned datasets, through large-scale distributed training on Qualcomm Cloud AI 100 and NVIDIA GPU clusters, all the way to optimized, deployment-ready artefacts for resource-constrained hardware in the vehicle. </p> <p> What awaits you? </p> <ul> <li> You build and maintain end-to-end ML pipelines using workflow orchestration tools: from data ingestion to distributed training, evaluation, model compilation, and deployment-ready artefacts. </li> <li> Furthermore, you engineer petabyte-scale data pipelines that consume domain datasets, transforming raw MDF4 (.mf4) and MCAP log files into training-ready formats. </li> <li> 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. </li> <li> Also, you manage experiment tracking, hyperparameter tuning and model registry, enforcing reproducibility, lineage, and approval gates from experiment to production. </li> <li> You develop and maintain model compilation and optimisation pipelines targeting in-vehicle Qualcomm Snapdragon Ride chips and/or NVIDIA automotive SoCs. </li> <li> On top, you operate observability stacks, providing dashboards, data-drift alerts, pipeline SLOs, and log aggregation. </li> </ul> <p> What should you bring along? </p> <ul> <li> University degree in Computer Science, Engineering, or a related field. </li> <li> 3–5 years of hands-on ML infrastructure or MLOps experience. </li> <li> Strong Python skills; experience with hermetic build systems (e.g., Bazel) is a plus. </li> <li> Production Kubernetes experience, including deploying and debugging workloads, writing Helm charts, and managing accelerator node pools. </li> <li> Working knowledge of ML pipeline orchestration, experiment tracking, and hyperparameter optimization. </li> <li> Hands-on experience with infrastructure-as-code for AWS (e.g., Terraform) and automotive measurement data, such as MDF4 or MCAP. </li> <li> Comfortable with relational databases (e.g., PostgreSQL) for metadata stores and experience with dataset management tools, functional-safety awareness (ISO 26262), or AUTOSAR Adaptive. </li> </ul> <p> Are you excited to shape the future of automotive AI infrastructure? Apply now! <br/> Find out more about Artificial Intelligence at the BMW Group here. <br/> </p> <p> Note: Please apply exclusively online via our career portal. Applications through other channels (especially email) cannot be considered. </p> <p> What do we offer? </p> <ul> <li> Challenging projects with which we shape the mobility of tomorrow together. </li> <li> Wide range of personal and professional development opportunities. </li> <li> Attractive, fair and performance-related remuneration. </li> <li> High level of job security. </li> <li> Annual special payments such as vacation pay, Christmas bonus, and profit sharing. </li> <li> Flexible working hours including six weeks annual leave and overtime compensation. </li> <li> Discounted BMW &amp; MINI conditions. </li> <li> Many other benefits at bmw.jobs/benefits </li> </ul> <p> Earliest starting date: from now on </p> <p> Type of employment: unlimited </p> <p> Working hours: full-time </p> <p> If you apply, the next stages of the recruiting process include an online test and then technical interviews with the hiring manager (either virtual or in person). </p> <p> You can find helpful tips on your application and the application process here. </p> <p> At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants. Learn more here. </p>