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NEXTMOVEFDE careers · United States

Senior/Staff Software Engineer, Perception

Technologies

C++ · Python · OpenCV · CUDA · TensorRT · Docker · Kubernetes · TensorFlow · PyTorch · LIDAR

About Gatik AI

Builds and operates driverless middle-mile freight networks for retailers and CPG shippers using fixed-route Level 4 medium-duty trucks.

Series C

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Deployment team leadership · Evidence for this classification:

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 Staff Engineers with expertise in classical and modern computer vision techniques to lead or actively contribute to the architecture, design, implementation, and delivery of a multi-modal perception system. The ideal candidate will be a software expert who has overseen a process from the R&D phase through product shipment and has a passion for leading teams and developing real-world solutions. This role is onsite at our Santa Clara, CA office. What you'll do Design and implement key components of perception system such as object detection, object tracking, and multi-sensor fusion Build software infrastructure to enable learning algorithms to leverage
More from the job description

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 Staff Engineers with expertise in classical and modern computer vision techniques to lead or actively contribute to the architecture, design, implementation, and delivery of a multi-modal perception system. The ideal candidate will be a software expert who has oversee [... source excerpt omitted ...] cess from the R&D phase through product shipment and has a passion for leading teams and developing real-world solutions. This role is onsite at our Santa Clara, CA office. What you'll do Design and implement key components of perception system such as object detection, object tracking, and multi-sensor fusion Build software infrastructure to enable learning algorithms to leverage large scale image/LIDAR data Design and write highly optimized pipelines for data pre-processing, model training, data post-processing, inferencing etc. Train perception models, evaluate their performance, investigate and fix performance bottlenecks Develop scalable training and evaluation tool [... source excerpt omitted ...] 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 unmanne

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