AI Research Scientist, Mapping

Who we areGatik, 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 roleWe'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 doWork on the Offline and Online Mapping Research tracksDefine the business metrics for Mapping assessment Continuously adjust the optimal Mapping feature format in collaboration with stakeholdersWork on the architecture design and implementation of Mapping modulesMine and/or generate Mapping evaluation data, including sudden Map changes Mitigate the negative effect of Mapping UncertaintyParticipate in the AI Research team activities targeting internal education and external scientific imageWork closely with the Production teams to push your idea into the deploymentPropose new ideas and build on top of state-of-the-art knowledgeWhat we're looking forYou have a Ph.D. in one or more of the following areas: Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related fieldYou 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 includingVarious formats of maps (rasterized, vectorized)Modular and end-to-end approachesHolistic scene understandingDifferent types of prior mapExperience in estimation and handling of Mapping UncertaintyStrong foundation in data structures, algorithm design, and complexity analysisExpertise 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!More about GatikFounded in 2017 by experts in autonomous vehicle technology, Gatik has rapidly expanded its presence to Mountain View, Dallas-Fort Worth, Arkansas, and Toronto. As the first and only company to achieve fully driverless middle-mile commercial deliveries, Gatik holds a unique and defensible position in the AV industry, with a clear trajectory toward sustainable growth and profitability.We have delivered complete, proprietary AV technology - an integration of software and hardware - to enable earlier successes for our clients in constrained Level 4 autonomy.  By choosing the middle mile – with defined point-to-point delivery, we have simplified some of the more complex AV challenges, enabling us to achieve full autonomy ahead of competitors. Given extensive knowledge of Gatik’s well-defined, fixed route ODDs and hybrid architecture, we are able to hyper-optimize our models with exponentially less data, establish gate-keeping mechanisms to maintain explainability, and ensure continued safety of the system for unmanned operations.Visit us at Gatik for more company information and Careers at Gatik for more open roles.Notable NewsForbes: Forget robotaxis. Upstart Gatik sees middle-mile deliveries as the path to profitable AVsTech Brew: Gatik AI exec unpacks the regulations that could shape the AV industryBusiness Wire: Gatik Paves the Way for Safe Driverless Operations (‘Freight-Only’) at Scale with Industry-First Third-Party Safety Assessment FrameworkAuto Futures: Autonomous Trucking Group Gatik Secures Investment From NIPPON EXPRESS HOLDINGSAutomotive News: Gatik foresees hundreds of self-driving trucks on road soon, and that's just the beginningForbes: Isuzu And Gatik Go All In To Scale Up Driverless Freight ServicesBloomberg: Autonomous Vehicle Startup Takes Off by Picking Off Easier RoutesReuters: Driverless vehicles on limited routes bump along despite US robotaxi scrutinyTaking care of our teamAt 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.