AI/ML Lead/Surgical Robotics - OTTAVA

AI/ML Lead / Surgical Robotics – OTTAVA Location: Santa Clara, California, United States of America Job Function Supply Chain Engineering Job Sub Function Automation Engineering Job Category Scientific/Technology Purpose The Engineer in Analytics and AI/ML for Digital Manufacturing is dedicated to advancing data‑driven manufacturing within our supply chain operations. This role involves leading the design, development, and implementation of analytics and artificial intelligence/machine learning solutions that provide both diagnostic and predictive insights to support real‑time performance management and informed decision‑making in intelligent, compliant operations. The successful candidate will collaborate with stakeholders across Manufacturing Engineering, Operations, Quality, J&J Technology, and R&D to deliver practical solutions that generate measurable business benefits and support scaling of future operations. Key Responsibilities Define technical requirements and architecture for analytics and AI/ML solutions across manufacturing environments (edge, OT, and cloud). Lead end-to-end delivery of analytics and ML solutions, including data ingestion, feature engineering, model development, validation, deployment, and lifecycle management. Design, implement, and operate production‑grade pipelines and inference (batch and real time) with monitoring and SLAs for latency, availability, and throughput. Translate manufacturing challenges (yield, downtime, quality, throughput) into measurable use cases with clear KPIs and expected ROI. Establish MLOps and governance practices (model versioning, experiment tracking, reproducibility, access control, audit trails) aligned to regulated manufacturing expectations (CSV, GxP where applicable). Partner with Manufacturing Engineering, Operations, Quality, IT, and R&D to prioritize and scale high‑value use cases (predictive quality, anomaly detection, predictive maintenance, process optimization) and translate them into scalable analytics; ensure adoption through documentation, playbooks, training, and stakeholder engagement. Apply statistical methods and experimentation (e.g., DOE, SPC, capability analysis) to quantify drivers, validate improvements, and support continuous improvement. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field. 7+ years of experience delivering analytics and/or ML solutions in production environments (manufacturing, supply chain, healthcare/MedTech, or other regulated industries preferred). Proven track record delivering ML/AI solutions into production at scale; experience in manufacturing or industrial/OT environments strongly preferred. Experience with manufacturing and industrial data sources (e.g., MES, OPC UA, PLC logs, telemetry, sensors) and translating domain requirements into deployable ML solutions. Strong Python skills; experience with ML libraries (e.g., scikit‑learn, TensorFlow, PyTorch) and data processing frameworks (e.g., Spark/PySpark). Hands‑on MLOps experience, including orchestration, CI/CD, model serving, monitoring/observability, automated retraining, and experiment tracking (e.g., MLflow). Proficiency in SQL and data modeling; familiarity with lakehouse/data lake patterns (e.g., Delta) and cloud data services (AWS or Azure equivalents), including secure architecture design. Applied expertise in time‑series and process analytics (anomaly detection, forecasting, classification/regression), including feature engineering and model interpretability/performance evaluation. Experience with model governance, validation, and compliance in regulated environments; familiarity with data governance, security, and role‑based access controls (CSV/GxP where applicable). Strong communication and stakeholder‑management skills, including the ability to document architecture/validation artifacts and present to technical and non‑technical audiences. Preferred Qualifications Experience with cloud analytics and lakehouse platforms and orchestration (e.g., Databricks, Spark/Delta) and effective collaboration with data engineering teams. Familiarity with digital manufacturing architectures and standards (e.g., ISA‑95/ISA‑88); unified naming/semantic standards are a plus. Experience with visualization and decision‑support tools (e.g., Power BI, Tableau) and building role‑appropriate dashboards. Other May require up to 10% of domestic and/or international travel. The attendance policy required for this role is Fully Onsite. Equal Opportunity Employer Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via , internal employees contact AskGS to be directed to your accommodation resource. Pay Transparency The anticipated base pay range for this position is $118,000.00 to $179,035.50. Additional description for pay transparency: Subject to the terms of their respective plans, employees and/or eligible dependents are eligible to participate in the following Company-sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance. Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)). This position is eligible to participate in the Company’s long-term incentive program. Subject to the terms of their respective policies and date of hire, Employees are eligible for the following time off benefits: Vacation –120 hours per calendar year Sick time - 40 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year Holiday pay, including Floating Holidays –13 days per calendar year Work, Personal and Family Time - up to 40 hours per calendar year Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child Condolence Leave – 30 days for an immediate family member: 5 days for an extended family member Caregiver Leave – 10 days Volunteer Leave – 4 days Military Spouse Time-Off – 80 hours Additional information can be found through the link below. #J-18808-Ljbffr