AI/ML Engineer Remote Nationwide or Hybrid in MN/DC

UnitedHealth Group•Eden Prairie, MN

5d•$72,800 - $130,000•Hybrid

About The Position

As an AI/ML Engineer within the Consumer Engineering division of the Chief Digital Office (CDO), you will play a critical role in shaping the future of our digital health platforms. This role is designed for a high-performing engineer with strong software fundamentals and a deep passion for building production-ready, scalable AI services. You will focus on the practical application of Generative AI techniques, designing end-to-end solutions that integrate seamlessly into our enterprise ecosystem. By leveraging modern data platforms and cloud-native architectures, you will help bridge the gap between complex machine learning research and reliable, consumer-facing applications that improve the lives of those we serve. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

Bachelor’s degree or equivalent experience
3+ years of experience in AI/ML or software engineering
3+ years of hands-on experience in backend development using Java (Spring Boot) and RESTful API design
3+ years of experience with databases, including SQL-based systems (PostgreSQL, MySQL, SQL Server) and exposure to NoSQL systems (MongoDB, DynamoDB)
2+ years of experience integrating applications via APIs, including supporting mobile or web client consumption
2+ years of proficiency in Python
2+ years of hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, or scikit-learn)
1+ years of experience productionizing models and working in cloud or distributed environments

Nice To Haves

Experience with Generative AI (GenAI) techniques and large language models (LLMs)
Experience with event streaming or messaging systems (e.g., Kafka)
Proven track record of building and maintaining automated ML pipelines (MLOps)
Demonstrated architectural awareness and the ability to influence technical direction
Familiarity with healthcare-related data privacy and security regulations (HIPAA)
Exposure to mobile app integration patterns (iOS/Android) and performance optimization for low-latency use cases
Exposure to cloud-native backend services and API gateways

Responsibilities

Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on the responsible use of AI
Build, deploy, and operate machine-learning models in production environments, ensuring high availability and performance
Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across the development lifecycle
Develop backend services and APIs using Java (Spring Boot) to support scalable AI/ML-powered applications and integrations
Design and implement data storage solutions, including relational databases (SQL) and NoSQL databases (MongoDB, DynamoDB), ensuring efficient data access for AI use cases
Collaborate with mobile and frontend teams to define API contracts and integration patterns that enable seamless delivery of AI-powered features into iOS and Android applications
Implement event-driven and streaming patterns (e.g., Kafka) to support real-time data processing and AI model feedback loops
Apply software engineering best practices, including unit testing, code quality, observability, and performance tuning across distributed systems
Evaluate emerging trends in AI and machine learning to inform solution design and drive strategic innovation within the division
Build and maintain scalable AI services, APIs, and pipelines, translating advanced models into reliable, enterprise-ready solutions
Implement MLOps practices, including CI/CD, monitoring, versioning, and rollback, to maintain model integrity and lifecycle
Ensure solutions meet security, privacy, and regulatory standards, upholding responsible-AI principles in a healthcare context