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ML Ops Engineer

ML Ops Engineer

Wenger & WatsonDelhi, India
3 days ago
Job description

Experience - 5 - 10 yrs

Locations - Bangalore, Chennai, Mumbai, Pune, Hyderabad

Key Responsibilities

Design, develop, and deploy machine learning models using AWS SageMaker for various business applications

Implement end-to-end ML pipelines from data preprocessing to model serving and monitoring

Build and maintain automated model training, validation, and deployment workflows

Optimize model performance, scalability, and cost-effectiveness in production environments

Create interactive ML applications and demos using Gradio for stakeholder demonstrations and user interfaces

Develop robust Python applications for data processing, feature engineering, and model inference

Build APIs and microservices for model serving and integration with existing systems

Implement model versioning, A / B testing frameworks, and continuous integration / deployment practices

ML infrastructure on AWS, including SageMaker endpoints, batch transform jobs, and processing jobs

Monitor model performance, data drift, and system health in production environments

Collaborate with DevOps teams to ensure reliable and scalable ML operations

Implement security best practices for ML systems and data handling

Technical Skills

Expert-level proficiency in Python programming with strong software development practices

Extensive hands-on experience with AWS SageMaker, including training jobs, endpoints, and pipelines

Proven experience with Gradio for building ML application interfaces

Strong background in machine learning algorithms, statistical modeling, and deep learning frameworks (PyTorch, TensorFlow, scikit-learn)

Experience with MLOps practices, model versioning, and deployment strategies

Deep understanding of AWS ecosystem (EC2, S3, Lambda, IAM, CloudFormation)

Experience with containerization technologies (Docker, Kubernetes)

Knowledge of data engineering tools and workflows (Apache Spark, Airflow, or similar)

Familiarity with infrastructure as code and CI / CD pipelines

Strong experience with version control systems (Git), code review processes, and agile development

Excellent problem-solving skills and ability to debug complex distributed systems

Experience with data visualization tools and techniques

Strong communication skills for presenting technical concepts to diverse audiences

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Ml Engineer • Delhi, India

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