• Grow out and lead a team of Deep Learning engineers • Steward the end-to-end planning, execution, and delivery of a scoped machine learning applied science agenda • Act as the primary point of contact with infrastructure and data pipeline teams • Exhibit strong judgement in derisking core hypotheses and updating research direction informed by ongoing advances in the state of the art

Role Description We are looking for a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale. The ideal candidate has both research depth and engineering pragmatism, with experience taking RL solutions out of the lab and into production where stability, safety, and ongoing improvement are critical. Key Responsibilities - Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments. - Develop, calibrate, and maintain simulation environments suitable for large-scale agent training. - Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods. - Engineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints. - Apply offline RL and imitation learning techniques where exploration is costly or unsafe. - Use RLHF, DPO, and related techniques for fine-tuning large language models when relevant. - Build scalable training infrastructure for distributed RL, including efficient experience collection and replay systems. - Optimize training stability and sample efficiency through algorithmic and engineering improvements. - Design rigorous evaluation protocols, including out-of-distribution and adversarial test cases. - Implement safety mechanisms such as constraint enforcement, conservative policies, and human-in-the-loop oversight. - Collaborate with applied scientists and product teams to identify high-value RL use cases. - Monitor deployed policies and models in production for drift, regression, and unintended behaviors, building the alerting and dashboards that surface issues before they meaningfully affect users. - Document methodology, design decisions, and operational characteristics for internal stakeholders. - Stay current with RL research and translate promising techniques into production-ready solutions. Qualifications - Master’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience. - Six or more years of combined RL research and engineering experience. - Strong proficiency in Python and modern deep learning frameworks. - Hands-on experience with at least one major RL library or in-house RL stack. - Solid understanding of probability, optimization, and the theoretical foundations of RL. - Experience designing and tuning reward functions in non-trivial environments. - Familiarity with simulation environments and large-scale experience collection. - Experience training neural network policies on GPU clusters. - Strong written and verbal communication skills. - Track record of shipping or publishing impactful RL work. Preferred Qualifications - Experience with RLHF for large language models. - Familiarity with multi-agent RL or hierarchical RL. - Exposure to robotics, control systems, or autonomous driving. - Publications in RL or related research venues. - Open-source contributions to RL libraries or environments. Requirements - 6+ years of experience. - 100% Remote (Continental United States). - Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party). - No new H1B sponsorship available; H1B transfers welcomed for qualified candidates. Benefits - Competitive base salary commensurate with experience, plus benefits.

Requisition Number: 2360711 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. The Optum Technology Digital team is on a mission to disrupt the healthcare industry, transforming UHG into an industry-leading Consumer brand. We deliver hyper-personalized digital solutions that empower direct-to-consumer, digital-first experiences, educating, guiding, and empowering consumers to access the right care at the right time. Our mission is to revolutionize healthcare for patients and providers by delivering cutting-edge, personalized and conversational digital solutions. We're Consumer Obsessed, ensuring they receive exceptional support throughout their healthcare journeys. As we drive this transformation, we're revolutionizing customer interactions with the healthcare system, leveraging AI, cloud computing, and other disruptive technologies to tackle complex challenges. Serving UnitedHealth Group's digital technology needs, the Consumer Engineering team impacts millions of lives through UnitedHealthcare & Optum. The Optum Technology Chief Digital Office (CDO) Leadership team is transforming Optum to be an industry-leading Consumer brand. We are on a journey towards delivering a best-in-the-industry consumer experience to our patients and providers by delivering personalized digital solutions that support our consumers throughout their healthcare journeys. This team is transforming to meet the moment - to begin radically altering the way our customers engage with the healthcare system using modern tech to solve some of the most complex problems experienced along the way. Serving all of UnitedHealth Group's digital technology needs, the CDO team is responsible for driving outcomes across nearly 30 million+ human lives with UnitedHealthcare insurance, a number which puts UHC at the top of the pack as the largest managed care provider in the United States. We are looking for a Lead AI/ML Engineer to code and develop software that deploys ML models and algorithms into production. This role communicates and presents complex analytics results and concepts to leadership and internal stakeholders. The role employs AI and/or ML techniques that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR). The engineer applies deep learning technologies to enable computers to visualize, learn, and respond to complex situations, and may adapt machine learning to areas such as artificial intelligence, robotics, and interactive user experiences. The role works with large-scale computing frameworks and data analysis systems. The role is expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using code for tool building and statistical analysis, using both general purpose software and statistical languages. 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. Primary Responsibilities: - Develop and implement AI and machine learning strategies across several healthcare domains - Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives - Develop and maintain strong relationships with stakeholders, customers, and partners internally and externally - Represent Consumer Engineering work and teams across Optum global leadership - Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations - Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/Generative AI where applicable - Create technical specifications and write high-quality, scalable, supportable code; review code of other engineers and mentor them to ensure all quality KPIs are met or exceeded - Demonstrate collaborative skills to work effectively with diverse teams - Possess deep expertise in modern software engineering practices including AI/ML/Generative AI, Agile methodologies, and DevSecOps to deliver daily product deployments using full automation from code check-in to production across the full SDLC lifecycle - Serve as a role model by leveraging these techniques to optimize solutioning and product delivery - Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery - Provide leadership and be accountable for the performance of managers and/or senior-level professional staff - Drive impact at the operational, local business unit, or market level 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: - Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline - 14+ years of experience in Software Engineering, Data Science, or Analytics, with at least 8 years in AI/ML engineering or related fields and the last 3 years focused on Generative AI technologies including OpenAI, Claude, Gemini, LangChain, Agents, RAG, Vector Databases, Prompt Engineering, and fine-tuning - Experience with AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, and Scikit-learn - Experience with cloud platforms such as AWS, Azure, and GCP - Experience with DevOps and CI/CD tools and practices including Git, Jenkins, Docker, and Kubernetes - Demonstrated experience leading and managing AI/ML teams and projects from ideation to delivery and evaluation - Hands-on experience in AI and driving the development of innovative AI and machine learning solutions - Proficiency in Python or other programming languages for data analysis and AI/ML development - Proven expertise in AI/ML techniques including deep learning, natural language processing, computer vision, recommender systems, reinforcement learning, and large language models Preferred Qualifications: - PhD in AI / ML, Engineering, Mathematics, Statistics, or a related discipline - Experience working with cross-functional and distributed teams in a global and diverse environment - Experience in mentoring, coaching, and developing AI/ML talent - Experience in establishing and enforcing AI/ML best practices, standards, and ethics - Experience in Realizing Value from AI/ML products as well as production ready product. - Proven history of delivering high-impact AI/ML solutions for real-world problems and use cases - Proven background in healthcare (AI) - Proven portfolio of AI/ML publications, patents, or awards - Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concepts to both technical and non-technical audiences - Proven solid analytical, problem-solving, and decision-making skills, with the ability to balance innovation and pragmatism - Proven passion for learning and staying updated with the latest AI/ML trends and research *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer 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 us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable. 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. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. #OptumTechPJ

• Build and operate the real-time inference service that scores models for the risk decision engine, with low latency and high availability as first-class requirements • Own model deployment infrastructure — registry and versioning, CI/CD with performance, bias, and consistency checks, shadow mode, and staged rollouts • Build model observability: availability, latency, and error monitoring, plus drift detection as a retraining trigger • Partner with Risk Data Science to take models from a clean development-to-production handoff through to production operation under MLP ownership • Implement experimentation capabilities such as champion/challenger and canary routing, and explainability outputs like SHAP attributions • Feel a strong sense of product ownership and actively seek responsibility — we self-organize on small and medium projects, and we want someone excited to help shape and build a brand-new platform team