AI Research Scientist, Mapping Mountain View, CA

Who we are :

Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly.

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 Mapping, including, but not limited to, online and offline mapping, map creation and maintenance, scene understanding, and uncertainty addressing technologies.

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 :

• Work on the Offline and Online Mapping Research tracks
• Define the business metrics for Mapping assessment
• Continuously adjust the optimal Mapping feature format in collaboration with stakeholders
• Work on the architecture design and implementation of Mapping modules
• Mine and / or generate Mapping evaluation data, including sudden Map changes
• Mitigate the negative effect of Mapping Uncertainty
• 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 : Mapping (preferable), Perception / Computer Vision, Statistics, Probability theory
• Deep knowledge of ML Mapping including
• Various formats of maps (rasterized, vectorized)
• Modular and end-to-end approaches
• Holistic scene understanding
• Different types of prior map
• Experience in estimation and handling of Mapping Uncertainty
• 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 (CVPR, ICCV, ECCV, NeurIPS, AAAI, IJCAI, ICLR, ICML, ICRA, CoRL, etc.)
• You are passionate about Autonomous Driving!

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.

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