Ready to drive the future? As part of the global Bertrandt Group, our team of innovators tackles cutting-edge projects across ADAS, Autonomous Driving, Electric Mobility, and Manufacturing Support, transforming complex issues into sustainable, connected solutions. With the strength of a global network of over 14,500 colleagues in 50+ locations, Bertrandt US combines deep expertise in Electronics, Product Engineering, Physical, and Production & After Sales.
Join us in engineering tomorrow’s mobility today. General
Benefits:
Complete and comprehensive benefits package including Med/Dent/Vision Employer paid STD/LTD/Life 401k Retirement program Generous paid vacation/sick/holidays Creativity encouraged in a fun, friendly work environment __________________________________________________________________________________________________________________________________ Data Engineering & Data Processing
- Design and develop scalable ETL/ELT pipelines for ingesting, transforming, and processing structured and unstructured data.
- Build and optimize data pipelines using Databricks, Spark, SQL, and cloud-native AWS services.
- Implement data quality, validation, lineage, and monitoring processes.
- Support medallion/lakehouse architecture patterns including bronze, silver, and gold data layers.
- Develop data pipelines to support AI/ML, GenAI, and RAG workloads, including document ingestion and embedding generation workflows. Machine Learning & Modeling
- Design and implement scalable ML models for classification, regression, clustering, forecasting, and recommendation systems.
- Apply advanced techniques including deep learning, ensemble learning, NLP, Generative AI, and LLM-based solutions where applicable.
- Conduct model evaluation, tuning, validation, and performance optimization using industry best practices.
- Develop and train models within Databricks ML and/or AWS SageMaker leveraging distributed computing and scalable cloud infrastructure.
- Build reusable feature engineering and model training pipelines.
- Develop Retrieval-Augmented Generation (RAG) solutions integrating LLMs with enterprise knowledge sources and vector databases. Cloud & MLOps
- Deploy and manage ML and GenAI models using AWS SageMaker and Databricks, including endpoint configuration, monitoring, and retraining workflows.
- Utilize Databricks MLflow for experiment tracking, model registry, and deployment automation.
- Implement and support vector database solutions for semantic search and RAG architecture.
- Collaborate with DevOps and platform teams to implement CI/CD pipelines for ML, GenAI, and data workloads.
- Automate operational workflows and optimize cloud resource utilization, scalability, reliability, and security. Deliverables
- Production-ready ML and GenAI solutions with supporting technical documentation.
- Scalable ETL/ELT pipelines and curated datasets.
- End-to-end Databricks notebooks, jobs, and workflows.
- Feature engineering pipelines and reusable ML components.
- RAG pipelines integrated with vector databases and enterprise knowledge sources.
- Weekly status reports and participation in Agile sprint ceremonies.
