Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together. As a Sr AI/ML Engineer within Optum Technology, you will be at the forefront of driving enterprise-scale artificial intelligence and machine learning innovations. You will collaborate with cross-functional teams of data scientists, data engineers, and software architects to design, build, and optimize high-impact AI/ML solutions and Generative AI capabilities. Working with modern cloud environments, Databricks, Large Language Models (LLMs), and robust MLOps practices, you will translate complex business challenges into scalable, reliable, and production-ready AI systems that advance healthcare quality and operational excellence. Primary Responsibilities: • Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI • Leverage enterprise-approved AI tools and software engineering best practices to streamline workflows, automate tasks, and drive continuous improvement • Evaluate emerging technology trends to inform solution design, architectural strategy, and continuous innovation across enterprise platforms • Independently design end-to-end AI/ML architectures, translating ambiguous business problems into scalable, production-ready AI use cases • Implement robust MLOps practices, CI/CD pipelines, and automated testing for model versioning, deployment, monitoring, drift management, and observability • Establish reusable engineering patterns, architectural standards, and development workflows to accelerate enterprise-scale AI adoption • Make technical trade-offs around model quality, scalability, performance, cost, security, and maintainability across cloud and containerized environments • Lead technical design reviews and mentor engineers while partnering effectively with data scientists, data engineers, product teams, security, and operations You'll be rewarded and recognized 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: • Bachelor's degree or equivalent experience • 7+ years of software engineering or data engineering experience • 3+ years focused specifically on AI/ML solution engineering and operational deployment • 3+ years of experience with Python, SQL, data structures, algorithms, and enterprise software engineering practices • 3+ years of hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow • 3+ years of experience building scalable data processing solutions using Databricks, Spark, or PySpark on cloud platforms (Azure, AWS, or GCP) • 3+ years of hands-on MLOps experience, including model versioning, CI/CD pipelines, automated testing, production monitoring, drift management, and observability • 3+ years of experience building and deploying APIs, microservices, containerized applications (Docker, Kubernetes), and Git version control practices • 2+ years of hands-on experience developing Generative AI and LLM solutions, including RAG (Retrieval-Augmented Generation), embeddings, vector search, prompt engineering, and agentic workflows Preferred Qualifications: • Master's degree in Computer Science, Data Science, AI/ML, Engineering, Statistics, Mathematics, or a related field • Demonstrated experience taking ML/AI solutions from prototype through production deployment and operational support at enterprise scale • Experience establishing reusable engineering patterns and development standards across cross-functional tech teams • Proven ability to evaluate technical trade-offs around model quality, scalability, cost, security, and maintainability in cloud-native environments Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $120,100 - $214,500 annually based on full-time employment. We comply with all minimum wage laws as applicable. At UnitedHealth Group, our mission is to help people live healthier lives and help make the health system work better for everyone. Together, we are shaping the future of healthcare by harnessing technology and innovation to make care simpler to navigate, more affordable and more connected for the people we serve. We are committed to creating an inclusive workplace where everyone feels welcomed, valued, heard and respected, empowering people to bring their authentic selves to work and strengthening our collective impact through diverse talents, backgrounds, experiences and perspectives. UnitedHealth Group and its affiliated brands are an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment.

Requirements

Must-haves

Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI
Leverage enterprise-approved AI tools and software engineering best practices to streamline workflows, automate tasks, and drive continuous improvement
Evaluate emerging technology trends to inform solution design, architectural strategy, and continuous innovation across enterprise platforms
Independently design end-to-end AI/ML architectures, translating ambiguous business problems into scalable, production-ready AI use cases
Implement robust MLOps practices, CI/CD pipelines, and automated testing for model versioning, deployment, monitoring, drift management, and observability
Establish reusable engineering patterns, architectural standards, and development workflows to accelerate enterprise-scale AI adoption
Make technical trade-offs around model quality, scalability, performance, cost, security, and maintainability across cloud and containerized environments
Lead technical design reviews and mentor engineers while partnering effectively with data scientists, data engineers, product teams, security, and operations
Bachelor's degree or equivalent experience
7+ years of software engineering or data engineering experience
3+ years focused specifically on AI/ML solution engineering and operational deployment
3+ years of experience with Python, SQL, data structures, algorithms, and enterprise software engineering practices
3+ years of hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow
3+ years of experience building scalable data processing solutions using Databricks, Spark, or PySpark on cloud platforms (Azure, AWS, or GCP)
3+ years of hands-on MLOps experience, including model versioning, CI/CD pipelines, automated testing, production monitoring, drift management, and observability
3+ years of experience building and deploying APIs, microservices, containerized applications (Docker, Kubernetes), and Git version control practices
2+ years of hands-on experience developing Generative AI and LLM solutions, including RAG (Retrieval-Augmented Generation), embeddings, vector search, prompt engineering, and agentic workflows
UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment.

Nice-to-haves

Master's degree in Computer Science, Data Science, AI/ML, Engineering, Statistics, Mathematics, or a related field
Demonstrated experience taking ML/AI solutions from prototype through production deployment and operational support at enterprise scale
Experience establishing reusable engineering patterns and development standards across cross-functional tech teams
Proven ability to evaluate technical trade-offs around model quality, scalability, cost, security, and maintainability in cloud-native environments

Application prep

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Keywords to mirror

aimlmachine learningci/cdpythonsqlazureawsgcpdockerkubernetesllm

Platform: radancy
Effort: medium

Benefits

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401k