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Mysuru · Remote · 5-8 Yrs · Sep 30
1 views
Unknown · Bengaluru, India
20 open roles2 posted in 7d20 in 30d
Work-life balance 4.5Compensation & benefits 4.0Culture & values 4.5
Hiring: Engineering
What employees say
+ Good company to work for
− Great place if you are a performed
More reviews on the company profile.
Job description
Remote
Overview
Job Role: - ML Ops Lead
Responsibilities
- Design, deploy, and manage scalable, secure, and automated ML/AI platforms across Azure and AWS.
- Lead MLOps lifecycle model deployment, monitoring, retraining, CI/CD orchestration, and drift management.
- Build, maintain, and optimize ML workflows using Azure Machine Learning, Databricks, and AWS SageMaker.
- Integrate ML services with data platforms (Azure Data Lake, Cosmos DB, S3, DynamoDB, RDS).
- Implement governance, observability, compliance, and audit practices across ML and GenAI environments.
- Manage containerized workloads using Docker and Kubernetes (AKS/EKS).
- Develop and maintain Infrastructure as Code using Terraform, Bicep, CloudFormation, or CDK.
- Collaborate with stakeholders to resolve ML pipeline issues and ensure efficient production delivery.
- Conduct testing (unit/integration) as part of CI/CD pipelines via Azure DevOps or AWS CodePipeline.
- Apply security best practices RBAC, IAM, least privilege, authentication, and key management.
- Monitor systems using Grafana, Prometheus, Azure Monitor, and Log Analytics.
Qualifications
- Cloud Platforms: Azure (AI Services, ML, AKS, Functions) and AWS (SageMaker, Bedrock, Lambda).
- ML & AI: Strong in Python, TensorFlow, PyTorch, Scikit-learn, and end-to-end ML lifecycle management.
- GenAI Tools: Azure OpenAI, Bedrock, LangChain; understanding of prompt injection and jailbreak mitigation.
- IaC & DevOps: Hands-on with Terraform, Bicep, CloudFormation, CDK, Azure DevOps, CodePipeline.
- Security: IAM, RBAC, Azure Policy, AWS SCP, Key Vault, Audit Logging.
- Networking: DNS, Load Balancers, VPNs, VNets.
- Monitoring: Grafana, Prometheus, Application Insights, Azure Monitor.
- Databases: Azure SQL, Cosmos DB, AWS S3, RDS, DynamoDB, Redshift.
- Preferred Tools: GitHub Copilot, Cursor, Claude Code, M365 Copilot.
- Soft Skills: Solid problem-solving, stakeholder collaboration, and documentation abilities.
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Job application FAQ
Last updated 27 October 2026
- How do I apply for ML Ops Lead (Mysuru) at Epergne Solutions?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Epergne Solutions may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this ML Ops Lead (Mysuru) role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is ML Ops Lead (Mysuru) remote or on-site in Mysuru, Karnataka?
- This listing is marked remote with location Mysuru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this ML Ops Lead (Mysuru) role at Epergne Solutions?
- This is a lead ML Ops Lead (Mysuru) role. Key skills include Remote. Feedback AI highlights matched vs missing skills on your profile after signup.