Principal AI​/ML Engineer - Remote

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 to start Caring. Connecting. Growing together.

Optum Insight partners with payers, providers, governments and life sciences companies to simplify and enhance clinical, administrative and financial processes through software-enabled services and analytics, while advancing value-based care. Our differentiated products, technology insights, clinical expertise and analytics support the entire health system - ultimately delivering better experiences for consumers. Optum Insight Technology and Engineering is a critical function in Optum Insight driving the innovation and value we provide our customers and partners.

This team is focused on products, solutions, platform / enabling capability development, product development lifecycle, engineering excellence and connectivity to Optum Technology.

The Clinical Decision Support (CDS) Engineering team, a unit within the Optum Insight Technology organization is responsible for building commercial products helping payers and providers with administrative and clinician focused CDS solutions. We are seeking a principal AI/ML engineer who can bring deep expertise across the full development lifecycle of machine learning and generative AI-based solutions from design to development to MLOps.

CDS is an area that truly touches payers, providers, as well as members and one where you can have a huge impact on improving the healthcare system for everyone.

You’ll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

• Drive end-to-end Generative AI and Machine Learning projects that have a high degree of ambiguity, scale and complexity
• Design robust AI architectures, ensuring that systems are scalable, secure, and efficient. This involves selecting appropriate technologies, frameworks, and methodologies.
• Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in product ionizing the ML models
• Perform hands‑on analysis and modeling of healthcare data sets to develop insights that increase business value
• Run A/B experiments, gather data, and perform statistical analysis. Continuously assess the performance of AI systems, optimizing algorithms and models to improve accuracy and efficiency
• Establish scalable, efficient, automated processes for large‑scale data analysis, machine‑learning model development, model validation, ML operations
• Research and implement innovative machine learning approaches
• Mentor and help recruit AI/ML scientists and machine learning engineers to the team

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.

• Bachelors degree in Computer Science or related major
• 10+ years of industry/academic experience in machine learning or a related field
• 5+ years of building models for business application experience
• 5+ years of experience leading technical teams
• Proven advanced understanding of Deep Learning with applications in NLP and multimodal modeling
• Proven solid Python programming skills and experience with deep learning frameworks such as PyTorch or Tensor Flow and big data processing tools like Hadoop and Spark
• Practical experience with AI technology stacks and deployment and operations methodologies in public cloud (Microsoft Azure technology stack preferred)
• Experience with state‑of‑the‑art algorithms and…