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MLOps Engineer - Implementation(m/w/x)
Building and maintaining petabyte-scale ML pipelines, transforming raw log files for training at an automotive group. 3-5 years ML infrastructure experience and production Kubernetes expertise required. Hermetic build systems experience a plus.
Requirements
- University degree in Computer Science, Engineering, or related field
- 3-5 years ML infrastructure or MLOps experience
- Strong Python skills
- Experience with hermetic build systems (e.g., Bazel) (plus)
- Production Kubernetes experience
- Working knowledge of ML pipeline orchestration, experiment tracking, and hyperparameter optimization
- Hands-on experience with infrastructure-as-code for AWS (e.g., Terraform)
- Hands-on experience with automotive measurement data (MDF4 or MCAP)
- Comfortable with relational databases (e.g., PostgreSQL) for metadata stores
- Experience with dataset management tools, functional-safety awareness (ISO 26262), or AUTOSAR Adaptive
Tasks
- Build and maintain end-to-end ML pipelines
- Engineer petabyte-scale data pipelines
- Transform raw log files for training
- Build tooling for parallel data readers
- Build tooling for signal extraction
- Build tooling for multi-sensor stream synchronization
- Build tooling for dataset platform integration
- Manage experiment tracking
- Manage hyperparameter tuning
- Manage the model registry
- Enforce reproducibility and lineage
- Enforce approval gates for production
- Develop and maintain model compilation pipelines
- Develop and maintain model optimization pipelines
- Target Qualcomm Snapdragon Ride chips
- Target NVIDIA automotive SoCs
- Operate observability stacks
- Generate dashboards and data-drift alerts
- Manage pipeline SLOs and log aggregation
Work Experience
- 3 - 5 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Bazel
- Kubernetes
- Helm
- AWS
- Terraform
- MDF4
- MCAP
- PostgreSQL
- ISO 26262
- AUTOSAR Adaptive
Benefits
Bonuses & Incentives
- Performance-related remuneration
- Christmas bonus
- Profit sharing
Competitive Pay
- Overtime compensation
Learning & Development
- Personal and professional development opportunities
Job Security
- Job security
Flexible Working
- Flexible working hours
More Vacation Days
- Six weeks annual leave
Corporate Discounts
- Discounted BMW & MINI conditions
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MLOps Engineer - Implementation(m/w/x)
Building and maintaining petabyte-scale ML pipelines, transforming raw log files for training at an automotive group. 3-5 years ML infrastructure experience and production Kubernetes expertise required. Hermetic build systems experience a plus.
Requirements
- University degree in Computer Science, Engineering, or related field
- 3-5 years ML infrastructure or MLOps experience
- Strong Python skills
- Experience with hermetic build systems (e.g., Bazel) (plus)
- Production Kubernetes experience
- Working knowledge of ML pipeline orchestration, experiment tracking, and hyperparameter optimization
- Hands-on experience with infrastructure-as-code for AWS (e.g., Terraform)
- Hands-on experience with automotive measurement data (MDF4 or MCAP)
- Comfortable with relational databases (e.g., PostgreSQL) for metadata stores
- Experience with dataset management tools, functional-safety awareness (ISO 26262), or AUTOSAR Adaptive
Tasks
- Build and maintain end-to-end ML pipelines
- Engineer petabyte-scale data pipelines
- Transform raw log files for training
- Build tooling for parallel data readers
- Build tooling for signal extraction
- Build tooling for multi-sensor stream synchronization
- Build tooling for dataset platform integration
- Manage experiment tracking
- Manage hyperparameter tuning
- Manage the model registry
- Enforce reproducibility and lineage
- Enforce approval gates for production
- Develop and maintain model compilation pipelines
- Develop and maintain model optimization pipelines
- Target Qualcomm Snapdragon Ride chips
- Target NVIDIA automotive SoCs
- Operate observability stacks
- Generate dashboards and data-drift alerts
- Manage pipeline SLOs and log aggregation
Work Experience
- 3 - 5 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Bazel
- Kubernetes
- Helm
- AWS
- Terraform
- MDF4
- MCAP
- PostgreSQL
- ISO 26262
- AUTOSAR Adaptive
Benefits
Bonuses & Incentives
- Performance-related remuneration
- Christmas bonus
- Profit sharing
Competitive Pay
- Overtime compensation
Learning & Development
- Personal and professional development opportunities
Job Security
- Job security
Flexible Working
- Flexible working hours
More Vacation Days
- Six weeks annual leave
Corporate Discounts
- Discounted BMW & MINI conditions
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
BMW Group
Industry
Automotive
Description
Das Unternehmen bietet spannende Praktika im Bereich Markenerlebnis und Eventmanagement und legt großen Wert auf Gleichbehandlung und Chancengleichheit.
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