Sr AI/ML Engineer, Cloud & AI Solutions - Remote or Hybrid in MN or DC
Eden Prairie, Hennepin County, Minnesota, 55344, USA
Listed on 2026-05-31
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Software Development
AI Engineer, Machine Learning/ ML Engineer, Cloud Engineer - Software
Improve the lives of others while Caring. Connecting. Growing together.
Job Description - Sr AI/ML Engineer, Cloud & AI Solutions - Remote or Hybrid in MN or DC (2366313)
Sr AI/ML Engineer, Cloud & AI Solutions - Remote or Hybrid in MN or DC - 2366313
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities.
Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
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.
- 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 ope rationalise 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 optimise AI solution performance, cost, latency, and resource utilisation in production
- Collaborate with Dev Ops, MLOps, and infrastructure teams to ensure secure, scalable deployment and operations
- Stay current with advancements in AI/ML frameworks, Generative AI, and cloud technologies
You’ll be rewarded and recognised for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications- 4+ years of experience as a software, AI/ML or data engineer delivering cloud‑based solutions
- 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, Tensor Flow, scikit‑learn or Hugging Face Transformers
- Experience building distributed systems and cloud‑native applications
- Hands‑on experience with Generative AI, LLM‑based solutions, RAG architectures and agentic frameworks (e.g. Lang Chain, Llama Index)
- Experience with MLOps tooling such as MLflow, Kubeflow, Sage Maker, Azure ML or Vertex AI
- 3+ years of experience building and deploying machine learning, deep learning or Generative AI solutions
- Experience with vector databases (e.g. Pinecone, Weaviate, FAISS, pgvector) and embedding models
- Demonstrated…
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