AI/ML Engineer

Caring. Connecting. Growing Together.

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.

Primary Responsibilities:

Contributes to the development, testing, deployment, and maintenance of machine learning models and AI-powered systems for consumer-facing platforms, under the guidance of senior engineers.

Participate actively in the full AI lifecycle: contributing to brainstorming and conceptualization, rapid prototyping and experimentation, and writing high-quality, robust production code.

Assist with the implementation and management of cloud infrastructure for AI solutions, learning and applying Infrastructure as Code principle.

Utilize and contribute to reusable AI/ML platforms, components, and frameworks, helping to improve engineering efficiency.

Actively seek guidance and learn from senior engineers through code reviews, pair programming, and technical discussions.

Collaborate closely with product managers, designers, and other engineers to understand requirements, refine technical approaches, and deliver scalable, impactful AI solutions.

Stay current with the latest advancements in AI/ML and software engineering, evaluate new technologies, and propose innovative ways to tackle healthcare challenges.

Troubleshoot complex technical issues, identify root causes, and implement effective solutions in both development and production environments.

Contribute to a team culture focused on technical excellence, continuous learning, and curiosity.

Analyzes and investigates.

Provides explanations and interpretations within area of expertise.

Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so.

Required Qualifications:

Undergraduate degree or equivalent experience.

4+ years of professional software engineering experience with a significant focus on building and deploying production-grade AI/ML models and systems.

4+ years of AI/ML Expertise: Understanding of core AI and machine learning concepts, models, and algorithms, demonstrated through practical application and system design. Ability to explain complex ideas clearly.

Hands-on experience building applications leveraging LLMs and deploying them into a production environment (considering aspects like performance, cost, reliability, monitoring).

Proven growth in software design, data structures, algorithms, and writing clean, testable, and maintainable code.

Familiarity and hands-on experience with relevant technologies such as backend services (e.g., Python/Node.js/Java/Go), cloud platforms (AWS/GCP/Azure), front-end frameworks (e.g., React Native helpful), CI/CD pipelines, REST/WebSocket API development, and database technologies.

Practical experience or solid knowledge in various machine learning domains such as Natural Language Processing (NLP), Computer Vision, Personalization & Recommendation systems, and/or Anomaly Detection.

Proven ability to quickly learn new technologies and methodologies, comfortable working on tasks requiring exploration and tackling ambiguity.

Self-driven, take immense pride in your technical contributions, proactively tackle problems, own features end-to-end, and find satisfaction in building impactful solutions.

Solid desire to understand how and why things work, driving you to build better, more efficient systems.