Requisition Number: 2366939 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 AI is UnitedHealth Group's enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform. As a Senior AI/ML Software Engineer, you will be responsible for the design and implementation of cutting-edge AI/ML systems for real-world healthcare challenges at Optum; including problems around improving patient engagement through smart nudging, predicting onset and progression of disease, Large Language Model solutions for summarizing large scale patient information, and optimizing clinical trials using both structured and unstructured (text) data. As a senior engineer in charge of AI systems, you will apply state-of-the-art approaches for MLOps to ensure the performance, scalability and reliability of machine learning models serving our customers and build data pipelines that deliver real-time insights. Optum AI team members: - Have impact at scale: We have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone - Do ground-breaking work: Many of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development - Partner with world-class experts on innovative solutions: Our team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the world's top universities 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: - Own the inference and delivery of machine learning insights to multiple customers - Manage, monitor, and scale machine learning systems, delivering insights to multiple customers - Partner with cross-functional engineering teams to implement scalable, flexible pipelines that bring AI innovations into real-world products - Work with large-scale data and distributed computing frameworks to process and analyze high-volume healthcare datasets efficiently - Drive pipeline efficiency and reliability through profiling, refactoring and advanced engineering - Develop new data pipelines to improve ML model usage 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: - Bachelor of Science in computer science or related quantitative field - 5+ years of professional software engineering experience, with at least 3+ years building and operating production ML systems - Expert-level Python experience, including writing production-grade, testable, and maintainable code - Hands-on experience building and deploying APIs using FastAPI (or similar Python web frameworks) in a production environment - Solid experience deploying, managing, and scaling services in Kubernetes, including: - Containerization (Docker) - Helm or equivalent deployment tooling - Resource tuning, autoscaling, and failure recovery - Proven experience with MLOps practices, including: - Model deployment and versioning - Monitoring model performance, drift, and system health Preferred Qualifications: - Experience with AzureML, DataBricks, and Azure Kubernetes - Experience with distributed computing approaches - Expertise in ML Ops, for example, model monitoring, drift detection, and event-based model retraining - Proven solid technical communication skills - Proven ability and drive to learn independently - Proven problem-solving and analytical thinking - Proven ability to explain technical decisions to stakeholders #OptumTechPJ *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 $120,100 - $214,500 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. #optumaiscience 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

• High Voltage Substation Lead Primary Design Engineer responsible for whole Substation Design including General Layout, Sections, HV cable routing, Civil Work. • Guide drawings, earthing calculation…etc., with maximize efficiency and accessibility for maintenance and operation. • Develop equipment bill of quantities (BOQ) and contribute to technical specifications and data sheets Selection for HV substation components. • Compliance with updated regulation/standards. • Collaborate closely with Protection, Control & Automation (PCA) Engineers to ensure primary/secondary system integration. • Coordinate with Civil/Structural Engineers on foundation design, cable trenches, equipment plinths, and building requirements. • Interface with MEP Engineers for auxiliary systems including HVAC, lighting, fire suppression, and drainage. • Act as the primary technical point of contact for internal teams, clients, and third-party stakeholders on primary design matters.

Role Description - Hands-on experience in any language (C, C++, Python). - Very thorough understanding of AI/ML. - Good to have understanding of networking domain. - Hands-on experience in Docker container environment. - Experience in using open-source and commercial tools for development. - Well versed and habituated to work in an agile product development model using CI/CD practices. - Knowledge of software builds, build systems, and CI/CD pipelines. - Experience with test-driven development through unit tests and integration tests would be a big plus. - Dedication to work on customer issue reproduction and debugging of customer issues. - Excellent verbal/written communication skills, teamwork, and interpersonal skills. - Ability to interface and collaborate directly with various stakeholders, business partners, and vendors. - Must have a can-do attitude towards continuous learning and delivery challenges. - Very good command of English. Qualifications - Engineering degree in a technical field of study (e.g., computer science, electrical/ECE engineering, software-related discipline, etc.). - 8-12 years of experience in software development. Company Description

Role Description DDN is seeking a highly experienced Senior Staff Engineer specializing in AI Data Path & Storage to lead hands-on development and integration of advanced storage systems with next-generation AI inference pipelines. This role involves coding, prototyping, and rapidly iterating on solutions in close collaboration with architects to design and deliver high-performance data movement architectures. - Leverage NVIDIA’s NIXL (Inference Transfer Library) alongside the Infinia Data Intelligence Platform to enable ultra-low-latency, high-throughput data movement across GPU, memory, and distributed storage layers. - Involve workloads including KV cache management and vector database retrieval. - The ideal candidate brings deep expertise in distributed storage, GPU data paths, and large-scale system optimization, with a proven track record of building and shipping production-grade AI infrastructure. Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. - 12+ years of experience in storage systems, distributed systems, or performance engineering. - Proven track record of architecting and delivering large-scale, high-performance infrastructure systems. - Deep expertise in distributed storage architectures (object storage, scalable file systems, or cloud-native storage platforms). - Strong understanding of Linux I/O stack, filesystem internals, and storage protocols. - Extensive hands-on experience with NVMe, SSD optimization, and high-performance storage environments. - Strong experience with RDMA, InfiniBand, or other high-speed data transfer technologies. - Solid understanding of GPU computing concepts and CPU–GPU data movement patterns. - Proficiency in Python and/or C/C++, with advanced debugging, profiling, and performance tuning skills. - Demonstrated ability to optimize latency-sensitive, high-throughput production systems. Requirements - Lead the design and implementation of high-performance data movement pipelines using NVIDIA NIXL across GPU, CPU, and storage tiers. - Architect and drive integration of DDN Infinia with GPU-accelerated inference platforms for large-scale, real-time AI workloads. - Own end-to-end optimization of I/O paths between GPU memory and storage using technologies such as NVIDIA GPUDirect Storage, RDMA, and NVMe-over-Fabrics. - Define and implement multi-tier storage architectures (NVMe, SSD, object storage) optimized for inference latency, throughput, and scalability. - Lead development of advanced KV cache management strategies, including offloading, prefetching, and persistence across distributed storage layers. - Partner with AI/ML engineering teams to optimize inference performance in frameworks such as PyTorch and TensorFlow. - Establish benchmarking frameworks and lead performance tuning efforts for storage and data movement in production inference environments. - Diagnose and resolve complex system bottlenecks across storage, networking, and GPU subsystems. - Influence architecture decisions for distributed inference systems, ensuring scalability, resilience, and efficient data locality. - Drive engineering excellence through best practices in observability, performance monitoring, automation, and reliability engineering. - Mentor junior engineers and provide technical leadership across cross-functional teams. Preferred Skills - Hands-on experience with NVIDIA NIXL or similar data movement frameworks. - Experience with GPU-aware storage pipelines and GPUDirect Storage. - Strong understanding of AI inference systems, LLM serving architectures, and KV cache optimization. - Experience with Retrieval-Augmented Generation (RAG) pipelines and open vector search ecosystems. - Background in high-performance computing (HPC) or hyperscale distributed environments. - Expertise in caching strategies, memory tiering, and data locality optimization. - Experience designing disaggregated compute and storage architectures. What You’ll Work On - Leading the evolution of storage systems into GPU-native data layers for AI inference. - Building next-generation distributed AI infrastructure using NIXL and Infinia. - Driving performance breakthroughs in real-time LLM inference at scale. - Designing storage architectures for large-scale AI datasets and retrieval systems.