Senior AI/ML Engineer
Dolby Laboratories (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted on 7 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and operate ML-ready data pipelines and platform services supporting AI researchers and product teams across the full ML lifecycle.
- Deploy, monitor, and troubleshoot production AI/ML workflows on Kubernetes and Databricks at scale, ensuring reliability, latency, throughput, and cost targets.
- Develop reusable data platform APIs, SDKs, and frameworks; own data quality, governance, observability, and metadata management for enterprise-wide ML data assets.
Minimum Requirements
- 5+ years experience in data engineering, AI engineering, or related field with production ML pipeline ownership.
- Expert proficiency in Python, Scala, or Java programming languages.
- Hands-on experience with Databricks Lakehouse, Delta Lake, Apache Spark or equivalent distributed data processing, and production Kubernetes workloads.
- Strong experience with cloud platforms (AWS, GCP, or Azure), advanced SQL, relational and NoSQL databases, data modeling, and event-driven systems.
Ideal Candidate Profile
- Experienced in designing and operating scalable ML data pipelines enabling research and product ML workflows in production cloud-native environments.
- Comfortable with end-to-end ML lifecycle operations including training, testing, validation, deployment, and inference of AI models at scale.
- Solid understanding and hands-on with Databricks, distributed processing frameworks, Kubernetes operations, and cloud data architectures to optimize cost, performance, and reliability.