Join Optum, a global leader in health technology, and contribute to improving health outcomes for millions. As an AI/ML Engineer, you'll be instrumental in developing and deploying cutting-edge machine learning models and algorithms into production environments. This role offers a dynamic culture, collaborative peers, comprehensive benefits, and significant career development opportunities.

Optum is dedicated to advancing health optimization on a global scale, fostering a culture of inclusion, connection, and growth. Your work will directly impact communities by connecting individuals with the essential care, pharmacy benefits, data, and resources they need to thrive.

Lead a high-performing team of data scientists, cultivating an environment of innovation and collaboration.

Spearhead the design and development of sophisticated predictive models and machine learning algorithms.

Partner with business stakeholders to deeply understand and articulate their data requirements.

Translate complex business challenges into data-driven solutions, effectively communicating intricate analytical findings to both technical and non-technical audiences.

Continuously monitor model performance, driving improvements in predictive accuracy and insight generation.

Stay abreast of the latest advancements in data science and AI/ML, integrating novel methodologies into our workflows.

Champion data literacy across the organization, empowering teams to leverage data for informed decision-making.

Uphold the highest standards of data integrity and ensure strict adherence to privacy regulations.

This role requires a Bachelor of Engineering or an equivalent degree.

Experience in coding and developing software to deploy ML models into production is essential.

Proven ability to communicate and present complex analytics results to leadership and stakeholders.

Proficiency in AI and ML techniques, including but not limited to NLP, NLU, semantic understanding, intent classification, computer vision, deep learning, and ASR.

Strong experience with large-scale computing frameworks and data analysis systems.

Solid understanding of experimental methodologies, statistics, optimization, probability theory, and machine learning principles for tool building and statistical analysis.

Ability to work independently on complex issues and serve as a valuable resource to team members.

Familiarity with large-scale computing frameworks and data analysis systems is expected.