AI/ML Engineer

AI / ML Engineer

machine learning

AI-driven applications

AWS Cloud

Key Responsibilities

• Design and develop machine learning models for predictive analytics, classification, and anomaly detection.
• Implement NLP and computer vision solutions for scientific, clinical, and document intelligence use cases.
• Build and manage end-to-end MLOps pipelines for model training, deployment, and monitoring.
• Integrate AI models into business applications and APIs for seamless consumption by data products.
• Monitor model performance, retrain as necessary, and ensure explainability and compliance with governance standards.
• Work collaboratively with data engineers, data scientists, and DevOps teams to optimize workflows.
• Ensure adherence to HIPAA, GxP, and 21 CFR Part 11 data compliance standards in AI environments.
  

Technical Skills

• Core ML & AI Services: Amazon SageMaker, SageMaker Pipelines, SageMaker Studio
• Generative AI & NLP: Amazon Bedrock, Amazon Comprehend Medical, Amazon Textract, Hugging Face
• Data Processing & Automation: AWS Glue, Lambda, Step Functions, EventBridge
• Model Deployment: API Gateway, ECS/EKS for scalable inference endpoints
• Proficiency in Python, with experience using TensorFlow, PyTorch, Scikit-learn, or Hugging Face Transformers
• Strong understanding of MLOps, model monitoring, and CI/CD for ML workflows
• Familiarity with AWS Security tools (IAM, KMS, CloudTrail) and governance frameworks
  

Qualifications & Experience

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
• 5+ years of experience in machine learning engineering, data science, or AI solution development
• Proven experience building and deploying production-grade ML models on AWS
• Strong understanding of ML lifecycle management, data preprocessing, and feature engineering
• Experience collaborating in Agile environments with cross-functional data and engineering teams
  

Preferred Qualifications

• Experience in life sciences, healthcare, or pharmaceutical analytics
• Familiarity with bioinformatics or clinical data modeling
• AWS Certified Machine Learning – Specialty or AWS Certified AI Practitioner
• Knowledge of AI ethics, model explainability, and responsible AI principles