MLOps Engineer

Experience: 7+ Years

Location: Bellandur, Bangalore

Shift: 1:30 PM 10:30 PM

Work Mode: Monday - WFH and remaining( 4days - work from office)

Mandatory Skill: Azure Cloud Architecture

Key Skills

MLOps, Python, CI/CD, GitHub, Ansible, Azure DevOps, Azure Machine Learning, MLflow, Docker, Kubernetes, Computer Vision.

Role Overview

We are looking for an experienced MLOps Engineer with strong expertise in Python, Azure Cloud Architecture, and production-scale machine learning systems. The ideal candidate will be responsible for building, deploying, and maintaining scalable ML pipelines and automating the end-to-end machine learning lifecycle.

Key Responsibilities

1. Machine Learning & Python Development

- Develop solutions using Python, leveraging object-oriented and/or functional programming.
- Build, deploy, and support production-grade machine learning systems.
- Apply Computer Vision and Cognitive Services to enterprise AI solutions.
- Integrate ML models with unstructured data to support business use cases.

2. MLOps & ML Platform Engineering

- Design and maintain end-to-end MLOps pipelines covering model training, experiment tracking, versioning, deployment, monitoring, and automated retraining.
- Implement MLflow or equivalent tools for experiment tracking and model lifecycle management.
- Develop APIs for model training and inference, supporting batch and real-time processing.
- Automate ML workflows using CI/CD pipelines, GitHub, Azure DevOps, and Ansible.

3. Azure Cloud & Containerization

- Design and implement cloud-native ML solutions using Microsoft Azure.




- Build and deploy ML pipelines using Azure Machine Learning SDK.
- Work with Azure Machine Learning, Microsoft Fabric (where applicable), Docker, and Kubernetes.
- Manage scalable ML/DL workloads, including distributed training and parallel model execution.

4. Data Engineering & Performance Optimization

- Orchestrate large-scale machine learning and deep learning workloads using contemporary data engineering and container orchestration tools.
- Optimize model performance and perform hyperparameter tuning at scale.
- Work with data engineering technologies such as Azure Data Factory, Databricks, and Apache Spark.
- Apply knowledge of linear algebra, probability, statistics, and algorithms to machine learning problems.

5. Stakeholder Collaboration

- Collaborate with technical teams and business stakeholders to identify AI/ML opportunities.
- Develop solutions that improve business workflows and enable data-driven decision-making.
- Communicate complex technical concepts effectively to stakeholders at different organizational levels.

Required Skills
- Strong hands-on experience in MLOps and production-scale ML systems.
- Proficiency in Python programming.
- Mandatory experience in Azure Cloud Architecture.
- Experience with Azure Machine Learning, Azure DevOps, and CI/CD automation.
- Hands-on knowledge of GitHub, Docker, Kubernetes, and MLflow or equivalent tools.
- Exposure to Computer Vision, Cognitive Services, and unstructured data processing.
- Knowledge of Databricks, Apache Spark, and Azure Data Factory is preferred.

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