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’re currently looking for research scientists with specialized skills in Uncertainty definition, exploration, estimation, and addressing technologies to enhance our autonomous driving systems’ ability to understand and handle the uncertainty considerations. In this pivotal role, you’ll be instrumental in designing and refining the ML algorithms that enable our trucks to safely navigate and operate in complex, dynamic environments. You will collaborate with a team of experts in AI, robotics, and software engineering to push the boundaries of what’s possible in autonomous trucking.

What you’ll do

• Define the Uncertainty at the different levels of Autonomous Driving
• Estimate Data-dependent Uncertainty and detect anomalous inputs
• Estimate ML model-based Uncertainty and detect anomalous outputs
• Mine and/or generate out-of-distribution examples
• Mitigate the negative effect of uncertainty propagation
• Participate in the AI Research team activities targeting internal education and external scientific image
• Work closely with the Production teams to push your idea into the deployment
• Propose new ideas and build on top of state-of-the-art knowledge

What we’re looking for

• You have a Ph.D. in one or more of the following areas: Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related field
• You have at least 1-3 years of hands-on experience in one or more of the following areas: Autonomous Driving (preferable), Robotics, or Deep Learning in general 
• You have at least 1-3 years of research experience in one or more of the following areas: Uncertainty Estimation (preferable), Out-of-distribution, Statistics, Probability theory, Robustness theory 
• Deep knowledge of ML Uncertainty including
  • Experience in estimation, evaluation, and handling of Uncertainty
  • Dealing with data- and ML model-based Uncertainty 
  • Background in mining Anomalies and Out-of-Distribution realistic data
• Strong foundation in data structures, algorithm design, and complexity analysis
• Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like TensorFlow/PyTorch 
• Demonstrated ability to publish research findings in any of the top-tier technical journals and conferences (ICLR, ICML, NeurIPS, AAAI, IJCAI, ICRA, CoRL, CVPR, ICCV, ECCV, etc.)
• You are passionate about Autonomous Driving!