Sr AI/ML Engineer, Cloud & AI Solutions - Remote or Hybrid in MN or DC

UnitedHealth Group•Eden Prairie, MN

13h•$120,100 - $214,500•Hybrid

About The Position

As a Sr AI/ML Engineer within the Growth Office — Modernization & AI Acceleration, you will design, develop, and deploy machine learning and Generative AI solutions on a scalable, cloud-based environment that accelerates AI adoption across the organization. You will partner closely with engineering, data science, product, and business stakeholders to translate strategic initiatives into secure, high-performance AI solutions. This role combines hands-on AI/ML engineering, model development, and AI solution enablement to deliver meaningful business outcomes. 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

4+ years of experience as a software, AI/ML, or data engineer delivering cloud-based solutions
3+ years of experience building and deploying machine learning, deep learning, or Generative AI solutions
3+ years of programming experience in Python (additional experience in Golang, JavaScript, or Java)
2+ years of experience with cloud platforms such as Azure, AWS, or Google Cloud
1+ years of experience with security and compliance in cloud environments
Experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or Hugging Face Transformers
Experience building distributed systems and cloud-native applications

Nice To Haves

Hands-on experience with Generative AI, LLM-based solutions, RAG architectures, and agentic frameworks (e.g., LangChain, LlamaIndex)
Experience with MLOps tooling such as MLflow, Kubeflow, SageMaker, Azure ML, or Vertex AI
Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, pgvector) and embedding models
Demonstrated familiarity with model evaluation, prompt engineering, fine-tuning, and responsible AI practices
Demonstrated familiarity with DevOps, CI/CD pipelines, containerization (Docker, Kubernetes), and cloud monitoring tools
Proven solid problem-solving and analytical skills with the ability to propose innovative AI solutions
Proven excellent communication and collaboration skills across technical and non-technical team
Demonstrated passion for continuous learning in AI/ML and cloud technologies

Responsibilities

Design, develop, and deploy AI/ML and Generative AI solutions in a cloud-based environment with a focus on scalability, reliability, performance, and security
Build, fine-tune, evaluate, and operationalize machine learning and LLM-based models for production use cases
Collaborate with business and technical stakeholders to understand requirements and translate them into robust AI-driven technical solutions
Contribute to AI architecture and technical design, including model selection, data pipelines, MLOps tooling, and integration patterns
Develop and maintain reusable AI components, prompt patterns, RAG pipelines, and agentic workflows
Apply responsible AI practices including bias, fairness, privacy, and model evaluation throughout the lifecycle
Partner with cross-functional teams including data scientists, software engineers, product managers, and UI/UX designers
Establish and maintain coding standards, ML best practices, and quality assurance processes
Conduct code and model reviews, provide constructive feedback, and share knowledge with peers
Monitor and optimize AI solution performance, cost, latency, and resource utilization in production
Collaborate with DevOps, MLOps, and infrastructure teams to ensure secure, scalable deployment and operations
Stay current with advancements in AI/ML frameworks, Generative AI, and cloud technologies