- Robot type
- Autonomous Vehicle
- Location
- Santa ClaraCaliforniaUSA
- Job type
- Artificial Intelligence
- Posted
- Jan 15, 2024
- Salary
- $180,000–$260,000 a year
Senior Software Engineer, Perception
Job description
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…
Job responsibilities
- 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 tools and infrastructure
- Collaborate with other engineers to conduct system integration and tests
Job requirements
- Masters’ or Ph.D. degree in Computer Science, Electrical Engineering, Robotics or related field
- 7+ years of related experience
- 2+ years of professional experience working on Computer Vision using C++ and OpenCV
- Expert knowledge of modern C++ (C++11 or later) and Python
- Experience in deploying perception algorithms into real-world environments
- Familiar with NVIDIA software libraries such as CUDA or TensorRT
- Experience building testing and evaluation platforms
- Familiarity with deep learning applied to computer vision problems
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