Job Requirement | MLOps Engineer (Cloud Agnostic)
- Siro Clinpharm
- 5 - 10 years
- Kolkata
- 4 days ago
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Job Description
Job Description: MLOps Engineer (Cloud Agnostic)
Required Information:
1. Role: MLOps Engineer Cloud Agnostic
2. Required Technical Skill Set: Python, ML Engineering, CI/CD, Docker, Kubernetes, Terraform, MLflow/TFX, Feature Stores, Model Registry, Observability
3. No of Requirements: 1
4. Desired Relevant Experience: 5 to 10 Years
5. Location of Requirement: India Any Location
Desired Competencies (Technical / Behavioral Competency)
Must-Have
- Strong experience with end-to-end MLOps lifecycle: training, packaging, deployment, monitoring.
- Expert Python skills and ML frameworks: TensorFlow, PyTorch, Scikit-learn.
- Hands-on with CI/CD using GitHub Actions, GitLab, Jenkins, or Azure DevOps.
- Strong experience with Docker and Kubernetes.
- Experience with MLflow, TFX, or similar workflow frameworks.
- Knowledge of IaC (Terraform preferred).
- Experience with observability: metrics, logs, drift detection, tracing.
- Strong understanding of security best practices for ML workloads.
Good-to-Have
- Experience with Kubeflow, Argo Workflows, MLRun, or Seldon.
- Experience with Feature Stores and vector databases.
- Experience with Lakehouse platforms: Databricks, Snowflake, Delta Lake.
- Knowledge of Generative AI pipelines and LLM lifecycle.
- Professional certifications in Cloud, DevOps, or ML Engineering.
Responsibilities / Expectations from the Role
- Design and build cloud-agnostic MLOps pipelines.
- Implement CI/CD pipelines for ML lifecycle automation.
- Deploy ML models on Kubernetes-based serving platforms.
- Create reusable Terraform modules and workflow templates.
- Implement governance: versioning, approvals, lineage, drift monitoring.
- Work with Data Scientists to productionize ML models.
- Develop monitoring solutions for performance, cost, and reliability.
- Ensure end-to-end security, compliance, and access governance.
- Prepare documentation, runbooks, and guidelines for teams.
Role Details (For Candidate Briefing)
Reporting To: Project Lead / ML Engineering Manager
Team Size: 510 (flexible)
On-site Opportunity: Based on project needs
USP of the Role: Opportunity to deploy ML systems across any cloud environment.
Project Details: End-to-end MLOps frameworks for cross-cloud ML delivery and governance.
Interested candidates can share profile on
di********t@si**********m.com
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Back End DeveloperEmployement Type: Full timeContact Details:
Company: Siro ClinpharmLocation(s): Kolkata
Keyskills: ML Engineer Docker Ci/Cd Python Kubernetes Obsevability Terraform TFX MLflow
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