Job Function:
Supply Chain Engineering
Job Sub Function:
Automation Engineering
Job Category:
Scientific/Technology
All Job Posting Locations:
Santa Clara, California, United States of America
Job Description:
Johnson & Johnson RAD (Robotics and Digital) is seeking for a Staff Engineer AI & ML – OTTAVA, for our Santa Clara, Location.
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Purpose
The Staff 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 the 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, andoperateproduction-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.
- EstablishMLOpsand governance practices (model versioning, experiment tracking, reproducibility, access control, audit trails) aligned to regulated manufacturing expectations (CSV,GxPwhere 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,validateimprovements, and support continuous improvement.
Qualifications:
- Bachelors orMasters 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).
Required:
- Proventrack recorddelivering ML/AI solutions into production at scale; experience in manufacturing or industrial/OT environmentsstronglypreferred.
- 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 Pythonskills; experience with ML libraries (e.g., scikit-learn, TensorFlow,PyTorch) and data processing frameworks (e.g., Spark/PySpark).
- Hands-onMLOpsexperience, including orchestration, CI/CD, model serving, monitoring/observability, automated retraining, and experiment tracking (e.g.,MLflow).
- Proficiencyin SQL and data modeling; familiarity withlakehouse/data lake patterns (e.g., Delta) and cloud data services (AWS or Azure equivalents), including secure architecture design.
- Appliedexpertisein 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/GxPwhere applicable).
- Strong communicationand stakeholder-management skills, including the ability to document architecture/validation artifacts and present to technical and non-technical audiences.
Preferred:
- Experience with cloud analytics andlakehouseplatforms 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 to10% of domestic and/or international travel
- The attendance policy required for this role is Fully Onsite
Required Skills:
Preferred Skills:
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 Companys consolidated retirement plan (pension) and savings plan (401(k)). This position is eligible to participate in the Companys 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. https://www.careers.jnj.com/employee-benefits
