NVIDIA is seeking to transform the manufacturing and industrial automation sector with innovative AI and machine learning technologies
Requirements
- Familiarity with metrology practices and high-precision manufacturing workflows
- Knowledge of vision and signal-based measurement methods and metrology data workflows
- Expertise in quality and reliability engineering practices
- Proven track record in developing algorithms aimed at predictive analytics and machine learning
- Experience integrating with PLC/HMI/SCADA/MES environments and understanding OT constraints
- Experience with deep learning and data analytics algorithms
- Knowledge of distributed applications and Smart Factory standards
Responsibilities
- Establishing and growing a software team to develop and prototype key deep learning and data analytics algorithms
- Architecting infrastructure for installation, integration, and monitoring of various software applications on NVIDIA platforms
- Leading the development of “AI copilots” for manufacturing using NVIDIA’s NIMs and Blueprints
- Providing architectural input for distributed applications and Smart Factory standards to improve scalability, reliability, and availability
- Collaborating with robotics teams to build and validate autonomous systems before deployment
- Establishing processes for compliance, including functional validation and enterprise security
- Being responsible for the Engineering roadmap for “AI for Manufacturing” solutions, aligning technical directions with business outcomes
Other
- MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field (or equivalent experience)
- 10+ overall years of validated experience in industrial manufacturing involving the build and development of automated machines
- 5+ years of leading and managing control of planning, staffing, budgeting, and expense prioritization, as well as recommending and implementing changes to methods
- Strong communication skills with great attention to detail
- Experience collaborating with multiple departments to address common automation challenges
