Job highlights

- This role is responsible for model deployment,monitoring,reliability,and governance-aware MLOps practices across batch,real-time,and streaming use cases
- . o . Batch inference (scheduled scoring jobs)
- Experience Range: 4+ years in production ML / MLOps . Industry Preference: Banking / Financial Services (Regulated Setting) : ML Engineer / MLOps Engineer

Role Focus: Model Deployment, Monitoring & Production ML Location: Pune (Hybrid/Onsite as applicable)

Experience Range: 4+ years in production ML / MLOps

Industry Preference: Banking / Financial Services (Regulated Environment)

`Role Overview ` We are looking for an experienced ML Engineer / MLOps Engineer to operationalize machine learning models at scale. This role is responsible for model deployment, monitoring, reliability, and governance-aware MLOps practices across batch, real-time, and streaming use cases.

You will work closely with data scientists, data engineers, platform teams, and risk/compliance stakeholders to ensure ML models are production-ready,



observable, secure, and compliant throughout their lifecycle.

`Key Responsibilities 1. Model Deployment & Serving `

- Design and implement model deployment patterns including:

o Batch inference (scheduled scoring jobs) o Real-time inference (REST/gRPC endpoints) o Streaming or near-real-time inference where required
- Package models using Docker containers and deploy to Kubernetes or managed cloud services .
- Ensure scalable, reliable serving with proper resource allocation, autoscaling, and failure handling .
- Support A/B testing, shadow deployments, and blue-green or canary rollout strategies.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 ML Engineer / MLOps Engineer (Chennai)
🏢 Han Digital Solution
📍 Chennai