AI ML Ops Software Engineer (Bangalore Hybrid)
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level (4–6 yrs), Bangalore metro, and broad MLOps skillset create high applicant competition.
Role requires specialized MLOps, Databricks, and vector/RAG experience, limiting cross-industry transferability.
Explicit 4–6 years plus mandatory Databricks, MLOps, Kubernetes and cloud skills imply high strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable and reliable AI/ML Ops platforms and pipelines for production.
Implement and manage end-to-end AI/ML model deployment, including CI/CD pipelines, infrastructure provisioning, monitoring, retraining automation, and resource optimization.
Collaborate with cross-functional teams to bridge model development and production, ensuring data security, version control, and compliance.
Minimum Requirements
4-6 years of work experience in AI/ML Ops model deployment and platform engineering.
Hands-on experience with cloud platforms (preferably AWS), Kubernetes, Docker, Terraform, CI/CD, and monitoring tools.
Proficiency in AI/ML frameworks and tools including Databricks Lakehouse ecosystem, MLflow, LangChain, LangGraph, Vector Search, Knowledge Graphs.
Legally eligible to work in India on an ongoing basis.
Ideal Candidate Profile
Experienced in building and managing large-scale enterprise SaaS AI/ML Ops platforms handling petabytes of structured and unstructured data.
Strong technical background integrating AI/ML workflows within cloud environments and optimizing resource usage for cost and performance.
Practitioner of modern software engineering including infrastructure as code, observability, and secure data governance in AI/ML production pipelines.