Senior Machine learning Engineer
Robert Bosch GmbH (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 25–40 LPA
Posted on 8 Sept
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Job description
Structured overview of role & requirements
About This Role
- Own and optimize the full lifecycle of deep learning infrastructure supporting L2+ ADAS, including Azure storage, hybrid Kubernetes clusters, and compute resource management.
- Architect and enhance high-performance data pipelines and loaders for complex multimodal datasets to support scalable multimodal multi-task training.
- Design, maintain, and monitor robust CI/CD pipelines, performance dashboards, and embedded evaluation pipelines for model compression and edge device testing.
Minimum Requirements
- Bachelor's degree in Computer Science, Electrical Engineering, or related field; advanced degree is a plus.
- 5+ years industry experience in MLOps, Data Engineering, or Software Infrastructure focused on Deep Learning systems.
- Expert proficiency in Python with strong software design and architectural skills.
- Strong hands-on experience with Kubernetes, Docker, Azure ML and Storage/Networking, Ray, PyArrow, SQL, GitHub Actions, and monitoring tools like Grafana.
Ideal Candidate Profile
- Experienced senior engineer capable of independently managing complex deep learning infrastructure with measurable impact on compute efficiency and scalability.
- Skilled at bridging infrastructure, data engineering, and deep learning domains with deep expertise and broad software design knowledge.
- Offers strategic leadership in performance benchmarking, software quality governance, and scalable embedded evaluation to enable feature teams' success.