Physical AI Engineer - Lilly Medicine Foundry

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. Lilly is entering an exciting period of growth, and we are committed to delivering innovative medicines to patients around the world. LRL has increasing needs for in-house manufacture of material for clinical supplies and will therefore construct a new campus to manufacture Clinical Trial (CT) Active Pharmaceutical Ingredient (API) to meet needs for an expanding portfolio (more and new areas), to accelerate development timelines, and to enhance supply chain robustness. The brand-new facility also known as Lilly Medicine Foundry (LMF) will utilize the latest technology to augment the current clinical supply chain for small molecules (SM), oligonucleotides, peptides, and Antibody Drug Conjugates (ADCs), monoclonal antibodies and bioconjugates, and add new capabilities including mRNA. The new site will be built using the latest high-tech equipment, advanced highly integrated and automated manufacturing systems, and have a focus on minimizing the impact to our environment. What You’ll Be Doing: Job Description: As a Physical AI Engineer, in partnership with other teams you will deploy advanced AI models into robotic, computer vision and sensor-based systems that make the Lilly Medicine Foundry safer, faster and more resilient. You will build and integrate edge-to-cloud pattern that connects cameras, sensors, AGVs, co-bots, drones and quadrupeds to the Foundry data platform, manufacturing execution and closed-loop quality systems, and you will use simulation and digital twins to validate those systems before they reach GMP areas. You will work closely with cross-functional teams, including AI researchers, hardware engineers, OT/IT and automation engineers, Quality, HSE and safety experts, and technology and integration partners (e.g., NVIDIA, AWS), to ensure that our systems are not only high-performing but also safe, secure, compliant, adaptable, and scalable within dynamic production environments. Initial pilots will run in existing space and labs before moving to the Foundry site. Key Responsibilities: - AI Integration: Lead the deployment and integration of advanced AI models (such as machine learning, computer vision, generative AI and agents, and reinforcement learning) into robotic and sensing systems, including cameras, AGVs, co-bots, drones and quadruped robots, to enhance decision-making, task execution, and adaptability in real-world manufacturing environments. Priority use cases include vision-based changeover, cleaning and dryness verification; spill, lockout/tagout and intrusion detection; predictive maintenance; and site and lab environment monitoring. - Edge-to-Cloud Platform and Orchestration: Design, build and operate the reference architecture from sensor to decision (edge, connect, data, intelligence, experience): GPU edge inference on site, models trained in the cloud on AWS, data ingestion through OT/IT integration layers (e.g., Ignition, MQTT, AWS IoT Greengrass, Aveva PI, Azure IoT Hub), and data landed in the Foundry data platform, with orchestration and an ontology spanning all layers. Evaluate build, buy and hybrid options for edge hardware and edge-to-cloud software. - System Optimization: Collaborate with engineers and data scientists to optimize AI algorithms and models for real-time performance on edge hardware in robotics and vision applications, ensuring minimal latency and robust behavior under varying conditions. Manage the model lifecycle, including training, versioning, performance monitoring, drift detection and retraining. - Digital Twins and Simulation: Build and maintain sim-ready asset libraries from CAD data and the equipment registry, and use simulation platforms (e.g., NVIDIA Omniverse, Isaac Sim) to progress from static to dynamic digital twins of process areas, generate synthetic data for model training, and test robot, co-bot and AGV behavior and safety rules before deployment. Support twin-based use cases such as lockout/tagout and SOP guidance, wayfinding to equipment, virtual tours and XR training, and smart P&ID and maintenance. - Closed-Loop Quality Integration: Integrate vision and sensor outputs with manufacturing execution and quality systems so that detections flow into an exception queue with an audit trail of Quality judgment on every AI flag, including cleaning verification and changeover checks. Expose equipment and twin data to AI agents (e.g., through MCP servers on OT data platforms) and generate summaries of incidents for HSE and Quality review. - Verification and Validation: Develop and implement novel verification methods to test and validate the performance of AI-driven robotics and vision systems in complex manufacturing environments. This will include the design of new testing protocols and performance benchmarks that account for AI-specific behaviors, the use of simulation-based validation, and execution of validation in line with GxP and Computer System Validation requirements in partnership with Quality. - Safety & Risk Mitigation: Work with safety experts to develop and implement safety mitigations, ensuring that the robotics systems meet industry standards and regulations, particularly as AI-driven systems are deployed in unstructured or dynamic manufacturing environments. Apply and verify safety rules for AGVs and co-bots, integrate with safety controllers, and support HSE use cases such as lockout/tagout, near-miss analysis and early incident detection, ensuring any vision-based check meets HSE and Quality governance. - Governance, Cybersecurity and Data: Ensure solutions pass cybersecurity architecture review, apply enterprise data governance and classification to image, video and sensor data, and complete AI intake and risk assessment before deployment. - Deployment and Support: Oversee the deployment of robotics and vision systems into production operations, taking pilots from existing space and labs to the Foundry site as dependencies (such as site, instrument and camera connectivity and MES and ERP integration for AGVs) are met, and providing troubleshooting, technical support, and optimization as needed during the integration phase. - Partner and Stakeholder Collaboration: Work with technology and integration partners (e.g., NVIDIA, AWS, robotics, camera and drone vendors) to deliver partner-backed pilots, and evaluate which partner services are production-ready for edge vision near GMP areas. Bridge Digital, Robotics, Facilities and Technology at Lilly teams, and contribute to pilot selection and sequencing based on value and dependencies. - Documentation and Reporting: Maintain thorough documentation for system deployment processes, safety protocols, validation and testing results, and AI integration methods. Provide regular reports to stakeholders regarding system performance and improvements. Basic Qualifications: - Bachelor’s degree in Robotics, Computer Science, Electrical Engineering, Mechatronics, or a related technical field. - Minimum of 5 years of experience in robotics, automation, or AI-driven systems deployment in a manufacturing or industrial setting. Additional Preferences: - Experience deploying computer vision or other AI models at the edge (accelerated inference, video analytics pipelines) with models trained in the cloud, ideally in a regulated or GMP manufacturing environment. - Experience with novel safety verification methods and risk analysis for autonomous or semi-autonomous systems, including AGVs and mobile robots, is highly desirable. - Strong programming skills in Python, C++, or ROS (Robot Operating System). - Knowledge of AI frameworks (TensorFlow, PyTorch, OpenCV, etc.) and model optimization and serving tools (e.g., ONNX, TensorRT, Triton). - Knowledge of industrial communication protocols (e.g., OPC-UA, MQTT, Modbus, Ethernet/IP). - Experience with industrial controls systems and Safety Controllers. - Experience with edge AI and GPU platforms (e.g., NVIDIA Jetson, DeepStream) and with edge-to-cloud architectures for vision and sensor data. - Experience with cloud services for IoT, data and machine learning (e.g., AWS IoT Greengrass, SageMaker, S3, GPU compute); familiarity with enterprise data platforms (e.g., Databricks, Microsoft Fabric). - Familiarity with OT/IT data integration and historian platforms (e.g., Ignition, Aveva PI, HighByte) and manufacturing execution systems. - Familiarity with simulation and digital twin tools (e.g., NVIDIA Omniverse, Isaac Sim, OpenUSD, CAD) and synthetic data generation. - Familiarity with generative AI, LLMs and agent frameworks (including MCP) applied to operations, quality or safety use cases. - Problem Solving: Strong analytical skills and a problem-solving mindset, with the ability to troubleshoot and optimize both hardware and software components of robotic systems. - Safety Knowledge: Familiarity with industry safety standards and risk mitigation strategies in robotics and automation (e.g., ISO 10218, ISO 13482, ISO 3691-4 for driverless industrial trucks and AGVs, ISO 13849, EN 61508), and with OT cybersecurity practices (e.g., IEC 62443). - Soft Skills: Excellent communication and teamwork abilities, with a customer-centric approach to solving technical challenges, and the ability to collaborate with external partners and bridge IT, OT, Quality, HSE and facilities teams. - Solid knowledge of Computer System Validation process and GxP requirements (e.g., GAMP 5, 21 CFR Part 11, EU Annex 11), including validation of AI-enabled systems. - Experience in pharmaceutical or biologics manufacturing operations (e.g., changeover, cleaning verification, API processes) and with integrating to quality and validation systems. - Demonstrated ability to analyze, anticipate, and resolve complex issues (technical, operational, or business-related) through sound problem-solving skills - Effectively prioritize and escalate issues. - Familiarity with data governance and AI risk-management practices for image, video and sensor data. - Demonstrated learning agility and curiosity. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL). Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $118,500 - $211,200 Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees. #WeAreLilly