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AI Research Scientist, Safety/Uncertainty

Gatik

Gatik

Software Engineering, Data Science
Mountain View, CA, USA
Posted on Sep 20, 2024

Who we are:

Gatik, the leader in autonomous middle mile logistics, delivers goods safely and efficiently using its fleet of light & medium-duty trucks. The company focuses on short-haul, B2B logistics for Fortune 500 customers including Kroger, Walmart, Tyson Foods, Loblaw, Pitney Bowes, Georgia-Pacific, and KBX; enabling them to optimize their hub-and-spoke supply chain operations, enhance service levels and product flow across multiple locations while reducing labor costs and meeting an unprecedented expectation for faster deliveries. Gatik’s Class 3-7 autonomous box trucks are commercially deployed in multiple markets including Texas, Arkansas, and Ontario, Canada.

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
  • 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!

More about Gatik:

With headquarters in Mountain View, CA and offices in Canada, Texas, Louisiana and Arkansas, Gatik is establishing new standards of success for the autonomous trucking industry every day. Visit us at Gatik for more company information and Jobs @ Gatik for more open roles.
Gatik News:
Taking care of our team:
At Gatik, we connect people of extraordinary talent and experience to an opportunity to create a more resilient supply chain and contribute to our environment’s sustainability. We are diverse in our backgrounds and perspectives yet united by a bold vision and shared commitment to our values. Our culture emphasizes the importance of collaboration, respect and agility.
We at Gatik strive to create a diverse and inclusive environment where everyone feels they have opportunities to succeed and grow because we know that together we can do great things. We are committed to an inclusive and diverse team. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.