Machine Learning Engineer - Amazon Web Services

Key Responsibilities

• Architect and implement end‑to‑end ML pipelines using AWS services (SageMaker, Glue, EMR) to process massive heterogeneous datasets.
• Develop and fine‑tune generative AI models, ensuring high performance and scalability for diverse business use cases.
• Collaborate with cross‑functional teams to translate business requirements into robust ML solutions and deliver actionable insights.
• Design model monitoring, governance, and continuous improvement workflows to maintain model quality and compliance.
• Mentor junior engineers and share best practices for ML engineering and DevOps on the cloud.

Requirements

• 5+ years of experience in production ML engineering, with a strong focus on generative AI.
• Proficiency in Python, SQL, and AWS ML services (SageMaker, Rekognition, Comprehend).
• Hands‑on experience with data engineering tools (Glue, EMR, Redshift) and big data processing.
• Solid understanding of model deployment, monitoring, and CI/CD pipelines for ML.
• Excellent communication skills and a collaborative mindset.