AI ML Engineer

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.

We are seeking a visionary AI Engineering Lead who excels at the intersection of advanced AI expertise, strategic thinking, and impactful leadership. This role is ideal for someone who can architect and deliver enterprise-grade AI solutions, mentor AI engineering talent, and drive innovation in Generative AI. You will be instrumental in shaping our AI engineering culture, technology strategy, and customer-centric solutions, with a solid focus on accuracy, scalability, performance, and robust design.

Builder Responsibilities:

Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making.

Primary Responsibilities:

Lead the design, development, and implementation of scalable AI/ML solutions, leveraging Python, SQL, pandas, numpy, and modern ML frameworks (TensorFlow, PyTorch, Scikit Learn)

Oversee end to end ML workflows-from data preparation, feature engineering, EDA, and model development to evaluation, deployment, and continuous monitoring

Guide model selection, optimization, and tuning, ensuring solutions balance performance, explainability, cost, and Responsible AI principles

Build and maintain production grade ML pipelines with orchestration and experiment tracking tools such as MLflow, Feature Stores, ONNX, and vector databases

Lead drift analysis, observability, and model health monitoring to ensure ongoing accuracy, reliability, and robustness in production environments

Design and support scalable, multi cloud ML infrastructure (Azure/GCP primary, AWS optional), incorporating best practices for compute, storage, networking, and distributed data processing

Collaborate with data engineering teams to integrate real time and batch pipelines built on Synapse/Big Query, Dataflow/Databricks, and Kafka/EventHub/Pub Sub

Work closely with engineering, product, data science, and UX to translate business requirements into actionable technical solutions and architecture patterns

Review and guide the creation of architecture diagrams, C4 models, ADRs, and technical specifications as part of engineering governance

Mentor and coach data scientists and ML engineers on best practices in model development, experimentation, coding standards, optimization, and cloud native ML deployment

Ensure ML systems meet high standards of scalability, security, reliability, automation, observability, and operational excellence

Collaborate with front end teams where needed to ensure ML components integrate seamlessly with product workflows and user-facing experiences

Stay current with emerging AI/ML tools, frameworks, and research; evaluate applicability to current and future projects

Communicate technical concepts, design trade-offs, and recommendations clearly to both technical and non technical stakeholders, including leadership

Document methodologies, experiments, findings, and implementation details to ensure maintainability and knowledge sharing across teams

Comply with company policies, employment terms, and organizational directives related to work arrangements and project assignments

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 regards 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:

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field

6+ years of experience in Data Science, AI/ML, or a similar role

Experience with the full life cycle of AI/ML projects, including EDA, model development, tuning, and drift analysis

Hands-on experience in delivering production-grade AI/ML projects

Solid programming skills in Python, with experience in pandas, numpy, and SQL

Solid understanding of mathematical and statistical concepts

Proficiency in frameworks such as Scikit Learn, TensorFlow, and PyTorch

Proven excellent problem-solving and analytical thinking skills

Proven solid communication and collaboration skills to work effectively in a team environment

Preferred Qualifications:

Familiarity with the US Healthcare domain

Knowledge of Big Data technologies (PySpark, Hadoop) and data streaming tools (Kafka, etc.)

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.