MLOps Engineer

5 days ago

Anywhere in IndiaMultiple Locations NextJobHunt Full time ₹ 6,00,000 - ₹ 18,00,000 per year

Role : MLOps Engineer

Location : Pan India

Employment Type : Full-time

About the Role :

We are seeking a highly skilled MLOps Engineer to design, deploy, and maintain scalable machine learning systems across production environments. The ideal candidate will bridge the gap between data science and DevOps, ensuring that ML models are efficiently deployed, monitored, and continuously improved.

You will work closely with data scientists, software engineers, and cloud infrastructure teams to build automated, reliable, and high-performance ML solutions that drive business impact.

Key Responsibilities :

- Develop, deploy, and monitor machine learning models in production environments.

- Automate ML pipelines for model training, validation, and deployment.

- Optimize ML model performance, scalability, and cost efficiency.

- Implement CI/CD workflows for ML model versioning, testing, and deployment.

- Manage and optimize data processing workflows for structured and unstructured data.

- Design, build, and maintain scalable ML infrastructure on cloud platforms.

- Implement monitoring, logging, and alerting solutions for model performance tracking.

- Collaborate with cross-functional teams to integrate ML models into business applications.

- Ensure compliance with best practices for security, data privacy, and governance.

- Stay current with emerging trends in MLOps, AI, and cloud technologies.

Mandatory Technical Skills :

Programming & Frameworks :

- Proficiency in Python (3.x) and SQL.

- Strong understanding of ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.

- Experience in data modeling, software architecture, and ML algorithm optimization.

Databases :

- Hands-on experience with both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB) databases.

Model Lifecycle Management :

- Model tracking, versioning, and deployment using MLflow.

- Model monitoring and data drift detection using WhyLabs.

- Workflow orchestration using Kubeflow and Airflow.

- Containerization and orchestration with Docker and Kubernetes.

- Logging and real-time monitoring using Prometheus and Grafana.

APIs & Version Control :

- Experience developing and integrating ML modules via RESTful APIs.

- Hands-on experience with Git for version control and CI/CD workflows.

Data Processing :

- Ability to process unstructured data (text, image, audio) and extract meaningful insights.

Preferred Cloud & Infrastructure Skills :

Cloud Platforms :

- Strong knowledge of AWS (Lambda, API Gateway, Glue, Athena, S3, Iceberg) or Azure AI Studio for model hosting and scalable deployment.

- Experience with Infrastructure as Code (IaC) using Terraform or CloudFormation.

CI/CD & Automation :

- Proven experience integrating ML models into Git-based CI/CD pipelines.

- Familiarity with feature stores such as Feast or Tecton for managing ML features.

Big Data & Distributed Computing :

- Experience with Spark, Hadoop, Dask, or Apache Beam for large-scale data processing.

Education & Experience :

- Bachelors or Masters degree in Computer Science, Data Engineering, or related field.

- [4 to 8 ] years of experience in MLOps, Machine Learning Engineering, or related domains.

Why Join Us :

- Work with a cutting-edge team leveraging AI/ML at scale.

- Opportunity to influence the design of large-scale ML infrastructure.

- Collaborative environment with a strong focus on innovation and automation.

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