Tech Lead, Perception

Gatik AI•Mountain View, CA

About The Position

We are currently looking for an experienced Technical Lead with specialized skills in Computer Vision specifically related to Autonomous Driving applications - LiDAR, camera, and radar Perception technologies. As a key member of our team, you will be responsible for developing and implementing Machine Learning models that accurately detect and track the surrounding environment, thereby enabling safe and reliable behavior downstream processing for our AVs. In this pivotal role, you'll be instrumental in designing, implementing, and deploying the ML algorithms that enable our trucks to safely navigate and operate in complex, dynamic environments both on-vehicle and within simulation environments for validation. This position requires a strong technical and ML background, hands-on software engineering experience, and a knack for technically lead engineers. You will collaborate with a team of experts in AI Research, robotics, and software engineering to push the boundaries of what's possible in autonomous trucking.

Requirements

Ph.D. or highly qualified M.S. candidate in one or more of the following areas: Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related field
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
At least 1-3 years of research experience in one or more of the following areas: Perception (preferable), 2D and 3D Computer Vision, Statistics, Probability theory
At least 1 year of technical leadership experience inside an industrial setting
Experience in data science including data collection, analysis, hypothesis formulation and verification
Deep knowledge of Autonomous Driving Perception including 2D vs 3D Detection, Camera vs LiDAR vs Radar, BEV map, ML-based tracking, Sensor fusion, Sensor calibration, Sensor degradation
Strong foundation in data structures, algorithm design, and complexity analysis
Experience with latency analysis and optimization of safety critical software systems
Expertise in programming languages and tools critical for high-performance computing in Python/C++ including large-scale data processing, parallel programming, code optimization 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, IROS, etc.)
Passionate about Autonomous Driving!

Responsibilities

Develop and / or adjust existing state-of-the-art perception algorithms for autonomous vehicles to advance / complement research in sensor fusion, 3D object detection, segmentation, and tracking in complex dynamic environments
Work on multiple parts of the Perception ML pipeline: 2D and 3D, closed and open vocabulary detection, data-driven tracking, classification and segmentation
Design and implement sensor fusion, sensor degradation, and other safety-critical systems
Lead initiatives to collect, augment, and utilize large-scale datasets from sensors such as cameras, LiDAR, and radar for training and validating perception models under various driving conditions
Develop robust testing and validation frameworks to ensure the reliability and safety of the perception systems across diverse scenarios and edge cases
Conduct thorough validation and testing of ML models in simulation and real-world environments to ensure robust performance and generalization
Analyze model performance and identify areas for improvement, iterating on design and implementation to enhance prediction accuracy and reliability
Document model architectures, methodologies, and results clearly and concisely
Collaborate closely with the Data Engineering and AI Research teams to define project requirements, formulate innovative concepts, and co-design ML models and be responsible for their effective deployment in a real-world trucking environment
Participate in hiring process for and manage the top notch ML Perception engineers