Principal Machine Learning Researcher (Physical AI)
Tasks
- Build machine health monitoring anomaly detection and diagnostics
- Define research direction and technical standards
- Design machine learning models
- Develop hybrid physics-ML models
- Develop real time closed loop control and autonomy systems
- Develop unsupervised and self supervised learning techniques
- Formulate learning based prediction and control models
- Integrate learned models with physics simulation and digital twins
- Integrate machine learning models into production workflows
- Learn from in situ sensor data
- Model relationships between process inputs geometry and machine state
Perks/Benefits
- 401k
- Casual dress
- Company holidays
- Employer paid Medical Dental Vision Insurance
- Flexible work hours
- Free catered meals
- Life insurance
- Paid parental leave
- Paid vacation
- Relocation assistance
- Sick leave
- Stock options
Skills/Tech-stack
Anomaly Detection | C++ | Computational Geometry | Computer Vision | Deep learning | Digital Twin | Machine Learning | Model-Based Control | Model-Predictive Control | Multi-Modal | Multi-modal data | Physical systems | Physics-based Simulation | Predictive control | Python | Reinforcement Learning | Reinforcement Learning for Physical Systems | Robotics | Self-Supervised Learning | Self-supervised | Sensor fusion | Simulation | Supervised Learning | Unsupervised Learning
Education
Regions
Countries
States
Cities
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