AI & ML Engineer job in Atlanta

We are looking for a Machine Learning Engineer to join Experity’s Data & AI team. In this role, you will build, deploy, and optimize production-grade machine learning and Generative AI solutions that power our healthcare products. You will Design, Develop and Deploy scalable ML systems and work closely with Data Scientists, Software Engineers, Product Managers, and Platform teams to deliver meaningful outcomes for healthcare providers and patients.

What You’ll Do

• Design, develop, and deploy machine learning models and AI services that power Experity’s Intelligent healthcare products.
• Design and implement automated data collection, feature engineering, model training, evaluation, deployment, and monitoring ML pipelines to enable predictive analytics, recommendations, forecasting, classification, and automation.
• Develop APIs and production services using Python and FastAPI. * Build and operationalize Generative AI solutions, including RAG pipelines and AI powered assistants.
• Work with large-scale healthcare datasets and cloud-native data platforms.
• Implement MLOps best practices for model training, deployment, monitoring, and governance.
• Collaborate with cross-functional teams to translate business problems into AI driven solutions.
• Contribute to architecture, technical design, and engineering best practices. Qualifications Required

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI, or a related field.
• 3+ years of experience building and deploying machine learning solutions in production environments.
• Strong programming skills in Python and SQL.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience building APIs using FastAPI or similar frameworks.
• Hands-on experience with Snowflake and modern data platforms.
• Experience with AWS services such as SageMaker, S3, Lambda, RDS, DynamoDB, ECS/EKS, and API Gateway.
• Experience with Docker, Kubernetes, CI/CD pipelines, and MLOps practices.
• Experience with Generative AI, LLMs, RAG architectures, and vector databases.
• Experience in Healthcare, HealthTech, or SaaS environments.
• Familiarity with AI orchestration frameworks and agentic workflows.
• Experience with distributed data processing and ML platform engineering.