Key skills
Applied AI/ML engineeringAWS SageMakerDistributed computingAWS technologiesAI applications in healthcarePythonCI/CD workflowsDatabases NoSQLDatabases SQLAPIscontainerizationJavaSQLNoSQLAIMachine LearningMLLLMAWSDockerGitHub ActionsEC2LambdaS3CloudWatchSNSSQSSageMakerAPI GatewayGitHubCI/CD
About this role
Optum is a part of the UnitedHealth Group family, focused on making health care work better for everyone. They are seeking a Senior AI/ML Engineer to research, design, and develop software solutions that derive information from patient data and build systems for healthcare AI products.
Responsibilities:
- Research, design, and develop computer and network software or specialized utility programs such as health care documentation system; design, develop, and implement systems that derive information from patient data in a scalable, reliable, and cost-effective manner; analyze clinical data and determine the best designs on how to process the data; ensure the delivery of high-quality, maintainable, and efficient code; build systems designed to allow customers to effectively ingest and store patient-related data allowing data scientists and engineers to access this data with ease; and engage with customers to develop at least one Healthcare AI product, from ideation to product release
Requirements:
- Master's degree in Computer Science, Information Technology, or a related field
- 36 months of experience in the job offered or a computer-related occupation
- Applied AI/ML engineering
- Develop and deploy machine learning and large language model (LLM) solutions, including integrating real-time inference pipelines using AWS SageMaker
- Design automated evaluation workflows, supporting ML model refinement
- Design and managing distributed computing environments
- Build scalable systems using AWS technologies such as Lambda, S3, Step Functions, SQS, SNS, EC2, CloudWatch, or Batch to support large-scale data ingestion, processing, and AI workloads
- Design and develop AI applications in the healthcare domain including payer, provider, or health records
- Use modern programming languages such as Python or Java
- Manage CI/CD workflows and infrastructure provisioning using tools such as AWS Cloud Formation, GitHub Actions, and Artifactory
- Databases including NoSQL and SQL
- Transfer ML models in production cloud environments by implementing APIs and containerize services such as Docker, Artifactory, Amazon ECR, or API Gateway
- Work with data scientists, healthcare professionals, and product managers in designing the user experience for at least one healthcare related product