Key Responsibilities:

• Design, develop, and deploy machine learning models using AWS AI/ML services (SageMaker, Bedrock, Lex, Rekognition, etc.).
• Optimize and fine-tune ML models for performance, scalability, and cost-efficiency.
• Implement MLOps pipelines for automated training, deployment, and monitoring.
• Collaborate with data engineers to build robust data pipelines (Glue, Athena, Redshift, etc.).
• Work with AWS services like Lambda, Step Functions, ECS, and S3 to integrate AI/ML into cloud-native applications.
• Stay updated with the latest advancements in generative AI, LLMs, and deep learning.
• Provide technical guidance to clients and internal teams on AI/ML best practices.

Required Skills and Experience:

• 4+ years of hands-on experience in AI/ML model development and deployment.
• Strong proficiency in Python, TensorFlow, PyTorch, or scikit-learn.
• Experience with AWS AI/ML stack (SageMaker, Bedrock, Claude, Titan, etc.).
• Knowledge of MLOps tools (SageMaker Pipelines, MLflow, Kubeflow).
• Familiarity with big data technologies (Spark, Hadoop, Databricks) is a plus.
• AWS certifications (AWS Certified ML – Specialty) are highly desirable.
• Strong problem-solving skills and ability to work in fast-paced environments.