Behavior Prediction Engineer

Who we are

Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world’s first fully driverless commercial transportation service with Walmart. Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation. 

The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations. 

About the role

We are looking for talented ML engineers with expertise in classical and modern machine learning techniques for behavior prediction to own and actively contribute to the architecture, design, implementation, and delivery of a multi-modal prediction system. The ideal candidate will be a ML expert who has overseen a process from the R&D phase through product shipment and developing real-world solutions. 

This role will be onsite 5 days a week at our Santa Clara, CA office.

What you'll do

• Develop key modules of the behavior prediction system, focusing on accurately predicting the movements and actions of surrounding objects to enhance the decision-making capabilities of our autonomous vehicles.
• Create and maintain robust software infrastructure that enables the use of large-scale image and LiDAR data for learning algorithms, ensuring seamless integration and high performance.
• Design and write highly optimized pipelines for data pre-processing, model training, data post-processing, and inference, ensuring efficiency and scalability.
• Train advanced behavior prediction models, including LSTM, Transformer, and other relevant machine learning models. Evaluate their performance rigorously, identify and fix performance bottlenecks to achieve state-of-the-art results.
• Create scalable training and evaluation tools and infrastructure to support continuous improvement and rapid iteration of behavior prediction models.
• Work closely with other engineers to integrate behavior prediction systems into the broader autonomous driving stack and conduct comprehensive system tests to ensure reliability and safety.