Lead Data Scientist (Gen AI)

TL;DR

Lead Data Scientist (Gen AI & Digital Twin): Developing digital twins and GenAI-assisted predictive analytics for condition monitoring of heavy machinery with an accent on anomaly detection, edge deployment, and automated diagnostic workflows. Focus on optimizing deep learning algorithms on NVIDIA GPUs, implementing RAG-based LLMs, and integrating multi-modal telematics data.

Location: Chicago, Illinois, USA. Visa sponsorship is not available for this position.

Salary: $128,470 - $208,770

Company

The world's leading manufacturer of construction and mining equipment, focused on creating sustainable communities through innovation in heavy machinery.

What you will do

• Design and implement GPU-accelerated ML models (XGBoost, autoencoders, GANs) to identify fault patterns in timeseries sensor data.
• Develop onboard digital twins using NVIDIA architecture to simulate, predict, and optimize heavy machinery performance.
• Adapt and test algorithms for edge processing on Cat equipment leveraging NVIDIA Jetson.
• Develop Generative AI agents that synthesize telematics data to generate prioritized repair steps for identified faults.
• Integrate multi-modal outputs from monitoring analytics and asset history to create machine-specific context for AI assistants.
• Profile and tune deep learning algorithms for maximum efficiency on NVIDIA GPU architectures.

Requirements

• Must be based in the USA; visa sponsorship is not available.
• 8+ years of experience with advanced data analysis, machine learning (clustering, neural nets), and statistical methods.
• Extensive proficiency in Python and its data stack (NumPy, SciPy, pandas).
• Experience with heavy equipment engineering or handling high-frequency IoT sensor data (CAN bus J1939).
• Degree in Applied Statistics, Data Science, Computer Science, or a relevant Engineering field.
• Working knowledge of cloud technologies (AWS, Azure, or GCP) and version control via GitHub.

Nice to have

• Proficiency in Fine-tuning, Prompt Engineering, and Retrieval-Augmented Generation (RAG) for LLMs.
• Practical experience with onboard architecture (e.g., projects using Raspberry Pi).
• Experience operating in an Agile environment.

Culture & Benefits

• Comprehensive medical, dental, and vision benefits.
• 401(k) savings plans, Health Savings Account (HSA), and Flexible Spending Accounts (FSAs).
• Paid time off including vacation, holidays, and volunteer days.
• Career development support and tuition reimbursement.
• Incentive bonus, disability benefits, and life insurance.
• Parental and adoption benefits.