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Experience
8 - 13 Years
Job Location
Education
Any Graduation
Nationality
Any Nationality
Gender
Not Mentioned
Vacancy
1 Vacancy
Job Description
Roles & Responsibilities
You will sit within a high-performing AI squad, working closely with Data Scientists, AI Engineers, and platform teams to bring machine learning models into production at scale.
This role is ideal for someone who thrives at the intersection of engineering, AI, and operational excellence.
Key Responsibilities
- Own and implement the end-to-end MLOps lifecycle (CI/CD, model registry, monitoring, governance)
- Design and build CI/CD pipelines for ML systems ensuring secure, scalable deployments
- Lead model deployment strategies (batch, real-time, streaming) with robust rollback and release controls
- Establish monitoring & observability frameworks (model performance, drift detection, alerts)
- Ensure governance, compliance, and audit readiness across ML workflows
- Drive operational excellence, including incident management, runbooks, and reliability engineering
Desired Candidate Profile
8+ years in MLOps / ML Engineering / Data Engineering / DevOps
Strong experience with ML lifecycle management (MLflow, model registry, versioning)
Proven track record building CI/CD pipelines for ML systems
Hands-on experience with Python, cloud platforms, and production ML environments
Strong understanding of monitoring, observability, and model performance management
Experience working in regulated environments (financial services preferred)
Company Industry
- Legal
- Law Firm
Department / Functional Area
- IT Software
Keywords
- Lead ML Ops Engineer
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