Senior Machine Learning Engineer (MLOps) - Chennai - Hybrid

Anlage Infotech; Chennai District; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Anlage Infotech in Chennai, India, is seeking a seasoned ML Ops Senior Engineer to design and operationalize scalable ML deployment pipelines, integrating data engineering practices and automated deployment with robust model hosting and continuous training in production.

The role requires strong DevOps and software engineering skills, collaboration with data scientists and engineers, and a focus on data quality, scalability, and reliability across the ML lifecycle.

Qualifications

• Proven experience leading ML Ops deployments in production.
• Strong data engineering background for end-to-end pipelines.
• Experience with model hosting, continuous training, and monitoring.

Responsibilities

• Lead design and operationalization of scalable ML Ops solutions.
• Collaborate with data scientists and DevOps to integrate data pipelines with ML models.
• Implement and maintain infrastructure as code for ML deployments.

Skills

ML Ops

Data Engineering

Model deployment

DevOps practices

Cloud platforms

Tools

Docker

Kubernetes

Terraform

Ansible

Vertex AI

AWS

GCP

Azure

FastAPI

Flask

Job description

Azure, Docker, Terraform, Vertex AI, Google Cloud Platform, CKA (Certified Kubernetes Administrator), Ansible, FastAPI, AWS, Python, Flask

Leading the design and operationalization of scalable ML Ops solutions by integrating robust data engineering practices, automating deployment pipelines, managing model/data lineage, and ensuring reliable model hosting and continuous training in production environments.

Primary Skills: Python, Flask/Fast API, Docker, Kubernetes, Vertex AI, AWS, GCP, Azure.

We are seeking a highly skilled and experienced ML Ops Senior Engineer with a strong background in data engineering to join our dynamic team. The ideal candidate will be responsible for leading and implementing the deployment, monitoring, and management of machine learning models in production environments, while also possessing expertise in data engineering principles.

This role requires a deep understanding of both machine learning and data engineering concepts, as well as proficiency in software engineering and DevOps practices.

The ML Ops Senior Engineer will collaborate closely with data scientists, software engineers, and DevOps professionals to optimize the end-to-end ML pipeline, ensure model scalability, and maintain high availability of ML applications.

Responsibilities:

1. Lead the design, development, and implementation of ML Ops solutions to deploy machine learning models into production environments efficiently, leveraging data engineering best practices.
2. Collaborate with data engineers, data scientists, and software engineers to integrate data pipelines with ML models (including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous training & deployment, and automated pipelines) with best practices, ensuring data quality, reliability, and scalability.
3. Implement and maintain infrastructure as co