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AI/ML Engineer-Remote
About The Company Optum, a part of UnitedHealth Group, is a leading global organization dedicated to transforming healthcare through innovative technology solutions. Committed to improving health outcomes, Optum leverages advanced data analytics, artificial intelligence, and digital tools to connect individuals with essential care, pharmacy benefits, and health resources.
The company fosters a culture of inclusion, collaboration, and continuous growth, offering comprehensive benefits and career development opportunities to its employees. With a focus on advancing health optimization on a global scale, Optum strives to make healthcare more accessible, efficient, and effective for diverse communities worldwide.
About The Role The Lead AI/ML Engineer will play a pivotal role within Optum’s Value Connect team, which is developing an AI-first platform dedicated to value-based care. This platform utilizes cutting-edge machine learning, large language models, agents, and automation to enhance provider performance, care outcomes, and operational efficiency.
The successful candidate will provide hands-on technical leadership, designing and implementing scalable, production-grade AI/ML solutions that transform complex healthcare data into actionable workflows. This role involves collaborating with cross-functional teams including product managers, data scientists, clinical experts, and business stakeholders to develop innovative AI capabilities such as predictive models, conversational AI assistants, agentic workflows, and MLOps practices. The position offers flexibility to work remotely within the United States, with specific in-office requirements for employees in Minneapolis or Washington, D.C.
Qualifications
- Bachelor’s degree with 6+ years, Master’s degree with 4+ years, or PhD with 3+ years of relevant experience in AI/ML engineering or related fields
- At least 3 years of hands-on experience developing, validating, tuning, and evaluating classical machine learning, deep learning, and Generative AI models
- Minimum of 3 years of professional experience writing production-level code in Python using modern ML/AI libraries
- Experience building and deploying AI systems utilizing RAG frameworks, vector databases, or orchestration libraries such as LangChain or LangGraph
- Proficiency in deploying, operating, and managing MLOps workloads on cloud platforms like Azure or AWS, including containerization
- Strong understanding of software engineering practices including version control (GitHub), CI/CD pipelines, and code reviews
- Lead the design, architecture, and end-to-end implementation of AI/ML, GenAI, RAG-based, and agentic solutions in healthcare
- Apply advanced machine learning, deep learning, statistical, and Generative AI techniques to solve complex clinical, operational, and financial problems
- Build, validate, optimize, and fine-tune AI/ML models, including performance tuning, quantization, and cost optimization strategies
- Develop and maintain production-grade APIs (e.g., FastAPI, REST) to expose AI capabilities at scale
- Establish and own MLOps practices, including model versioning, lifecycle management, monitoring, logging, and drift detection to ensure reliability
- Deploy AI workloads on cloud platforms such as Azure or AWS using containerization, Databricks, PySpark, and modern data platforms
- Implement engineering best practices for software quality, security, responsible AI, and conduct design and code reviews
- Collaborate with product teams, data scientists, clinical stakeholders, and business units to develop innovative solutions
- Mentor engineering team members and evaluate emerging AI technologies to ensure continuous platform enhancement
- Leverage enterprise-approved AI tools and technologies to automate workflows, streamline development, and improve platform capabilities
- Competitive salary ranging from $145,500 to $249,500 annually, based on experience and location
- Comprehensive benefits package including health insurance, dental, and vision coverage
- Incentive and recognition programs to reward performance
- Equity stock purchase options and 401(k) retirement plans
- Flexible remote work arrangements within the United States
- Opportunities for professional growth, training, and career development
