Virtusa - Artificial Intelligence/Machine Learning Engineer - AWS SageMaker

Key Responsibilities :

- Design, develop, train, and deploy machine learning and deep learning models for real-world business use cases

- Build end-to-end ML pipelines including data ingestion, feature engineering, model training, evaluation, and deployment

- Implement and manage ML workflows using AWS services such as SageMaker, S3, EC2, Lambda, Glue, and Step Functions

- Deploy models as scalable APIs using Docker, REST endpoints, and CI/CD pipelines

- Monitor model performance, drift, and retraining strategies in production

- Collaborate with data engineering teams to ensure high-quality, reliable data pipelines

- Optimize model performance, cost, and scalability on AWS infrastructure

- Ensure solutions meet security, compliance, and governance standards

Required Skills & Experience :

- 3+ years of experience in Machine Learning / AI development

- Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch)

- Hands-on experience with AWS ML stack, including :

1. Amazon SageMaker (training, endpoints, pipelines)

2. S3, EC2, IAM, Lambda

3. Glue, Athena, Redshift (nice to have)

- Experience with model deployment and MLOps practices

- Solid understanding of supervised, unsupervised, and deep learning techniques

- Experience with REST APIs, Docker, and Git-based version control

- Strong problem-solving and communication skills