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Tier-1 brand, mid-level ML role in Bangalore with broad skills attracts many qualified applicants.
Specialized ML and MLOps focus makes cross-industry fit moderate.
Mandatory 4+ years plus ML, MLOps, cloud and Kubernetes requirements make shortlisting strict.
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Design and deliver scalable generative AI microservices integrated with multiple applications and thousands of tenants in production.
Improve system efficiencies with automation covering capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
Collaborate with Product Managers, Architects, Data Scientists and Researchers to translate customer requirements into prototypes and production AI technologies.
Minimum 4+ years of professional experience in ML engineering focused on AI systems or services.
Experience designing and building distributed microservices on public cloud platforms such as AWS or GCP.
Familiarity with containerized deployment technologies including Kubernetes and Spinnaker.
Work Experience Required: Minimum 4+ years in relevant ML engineering roles.
Proven track record of delivering innovation at scale and operating distributed, scalable AI/ML systems.
Strong expertise with modern data storage, messaging and processing frameworks like Kafka, Spark, Hadoop, Docker.
Comfortable in cross-functional teams involving product, research and engineering collaborating to build ML-powered production applications.