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Eden Prairie

    Lead AI/ML Engineer - Eden Prairie, United States - Optum

    Optum background
    Description

    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 diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together.

    Optum AI is chartered to drive value on high impact enterprise AI problems, democratize AI through the enterprise ML platform, accelerate the adoption of Generative Artificial Intelligence (Gen AI) and drive Responsible AI. Projecting to deliver $8.4B of benefit value over the next 5 years through these efforts as well as reduce risk through safe, accurate, and unbiased AI, this is a key focus of the enterprise.

    You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

    Primary Responsibilities:

    • Conduct applied research experiments, build and test machine learning and deep learning models
    • Implement and design novel machine learning and deep learning approaches inspired by relevant literature
    • Build robust machine learning pipelines to support production processes
    • Implement online learning methods to optimize ML models in prospective pilot scenarios using approaches such as Multi-Armed Bandits and Reinforcement Learning
    • Process and transform source data to be used in machine learning pipelines, leveraging distributed computing environments and parallel processing approaches
    • Develop robust evaluation modules and automated reports
    • Conduct statistical analysis and create data visualizations
    • Design, plan, and prioritize experiments
    • Run machine learning experiments in distributed computing environments, leveraging parallel processing approaches
    • Communicate findings with business stakeholders and collaborate to develop solutions that meet customer needs
    • Develop code and model documentation and assist with model governance approvals

    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:

    • MS or PhD in computer science or a related quantitative field
    • 4+ years of machine learning and data science experience
    • 2+ years of experience leading ML projects
    • 3+ years of experience with Python, classical ML methods and deep learning, including deep learning frameworks such as PyTorch or Tensorflow
    • 2+ years leading projects with solid technical communication skills, including demonstrated technical leadership
    • 1+ years of hands-on experience with NLP approaches such as text embedding and text classification and using and evaluating LLMs/generative AI models

    Preferred Qualifications:

    • Experience with online learning approaches such as Multi-Armed Bandits and Reinforcement Learning
    • Experience with distributed computing approaches such as Spark
    • Experience with distributed ML model training with AzureML
    • Experience building and adjusting weighted model ensembles in online learning settings
    • Experience forking open-source projects and modifying source code
    • Familiar with clustering algorithms and recommendation systems
    • Experience working on collaborative software projects using GitHub

    *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.

    California, Colorado, Connecticut, Hawaii, Nevada, New Jersey, New York, Rhode Island, or Washington Residents Only: The salary range for this role is $104,700 to $190,400 annually. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. UnitedHealth Group complies with all minimum wage laws as applicable. In addition to your salary, UnitedHealth Group offers 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 UnitedHealth Group, you'll find a far-reaching choice of benefits and incentives.

    Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

    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.

    Diversity creates a healthier atmosphere: UnitedHealth Group is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.

    UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.



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