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Niche MLOps specialization and senior requirement reduce applicant density despite Chennai metro.
Requires automotive/B2B experience plus MLOps specialization, reducing cross-industry transferability.
Multiple explicit years requirements and mandatory cloud, containers, IaC, and ML production skills.
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Design and engineer data pipelines and infrastructure for enterprise-scale machine learning systems in Automotive and B2B contexts.
Deploy offline data scientist models into production ML systems using Databricks, ensuring auditability, versioning, and data security.
Evaluate and integrate new technologies to improve model performance, maintainability, and reliability, applying CI/CD and automation best practices.
7+ years of data analytics or business intelligence experience with 5+ years in model development, monitoring, and production.
Bachelor’s degree in Information Management, Computer Science, Business Administration, or relevant field.
Proven expertise in ML lifecycle management, including deployment, monitoring, retraining, and scaling of ML models.
Strong skills in Python programming, cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), infrastructure as code (Terraform, CloudFormation), and CI/CD tools (Jenkins, GitLab).
Experienced in managing ML models from development through production within Automotive or B2B industries.
Hands-on with Databricks platform and modern ML operational frameworks emphasizing auditability, versioning, and security.
Skilled at cross-functional communication with technical and business teams to translate requirements and track project progress.