Lead Data Scientist – Gen AI for Condition Monitoring Analytics
Core
Lead Data Scientist developing generative AI and predictive analytics models for condition monitoring of heavy machinery using digital twins and onboard edge computing.
Role type
Senior IC machine learning engineer (generative AI & predictive maintenance)
Builds
Digital twins, GenAI diagnostic agents, and real-time condition monitoring systems for heavy equipment
Domain
Industrial IoT, heavy equipment, predictive maintenance, generative AI
Deliverable
production ML models
Required skills
Generative AI & LLMs (fine-tuning, prompt engineering, RAG), Anomaly Detection, Time-Series Analysis, Python (NumPy, SciPy, pandas), GPU-accelerated ML (XGBoost, autoencoders, GANs), High-performance computing, Statistical process control, CAN bus protocols (J1939), Cloud technologies (AWS, Azure, GCP), Version control (GitHub), Agile methodologies
Preferred skills
Onboard architecture experience (e.g., NVIDIA Jetson, Raspberry Pi), Heavy equipment engineering background
Technologies
NVIDIA architecture, NVIDIA Jetson, XGBoost, Autoencoders, GANs, Python, NumPy, SciPy, pandas, AWS, Azure, Google Cloud, GitHub, CAN bus J1939
Responsibilities
Design and implement GPU-accelerated ML models for anomaly detection in high-frequency sensor data; Develop onboard digital twins to simulate and optimize heavy machinery performance; Adapt and test algorithms for edge deployment on Cat equipment; Develop Generative AI agents to synthesize telematics data for prioritized repairs; Profile and tune deep learning algorithms for real-time monitoring efficiency; Provide technical leadership and monthly status updates to sponsors and stakeholders
Seniority
Senior, hands-on IC