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AI Engineer

Belmont, CA
Experience: 7 years 
Software Development and Testing – (80%)

Software and Artificial Intelligence (AI) technologies & technical skills
Background in Deep Neural Network Learning, Computer Vision and Machine Learning
Strong programming skills with Python and TensorFlow/Pytorch PyTorch on on-premises compute and public clouds (e.g. AWS), Knowledge of generating features from sensor technology like camera, lidar, radar, GPS/ D-GPS and HD maps
Experience with data gathering, data quality, system architecture, coding best practices
Take initiative to launch projects with the ability to quickly learn and develop own ideas in an interdisciplinary environment
Extracting high level logical structure from low level, multi-dimensional data
Experience with different types of Neural Networks such as Transformers, CNNs, RNNLLMs, LSTMs, GNNs,
Experience with different ML paradigms such as supervised/unsupervised learning, reinforcement learning, self-supervised learning, and imitation learning paradigms and the latest research trends
Specification/Documentation of interfaces between software modules.
Programming languages/tools as Python, C++, Python, LaTex, Bash, Cmake, Git, Linux, familiar with data structures and algorithms, machine learning and math
Knowledge in using open-source libraries: OpenCV, OpenGL, TensorRT, Open3D, CUDA, Open3D, PCL
Project Management & leadership
Experience running one or more projects simultaneously.
Project managing tasks - manage timelines, budgets, resource planning, risk etc.
Effective at communicating with teams across cultures and in different times zones
Specialized Skills - Desired:
Experience with algorithm development for Autonomous Driving tasks including Perception, Sensor Fusion, Motion Prediction, Path Planning, End-to-End Driving, Simulation, V2X
Experience with current state-of-the-art technologies such as Vision-Language Models, Neural Radiance Fields, Embodied AI, Deep Sensor Fusion, Generative AI
Experience with AI/ML compute optimization techniques such as quantization, knowledge distillation, compilation, sparse computing.
Experience in programming concepts: Data filters/pipelines, multi-threading, programming for various types of SoC, real-time systems.
Experience in a regulated industries such as automotive, aerospace, medical devices etc.
Experience in one or more of the following technical areas:
Compute architectures and technologies.
Sensor technologies
Robotics
Broad knowledge of full vehicle interrelationships automotive systems and interfaces between them
High level of engagement and self-initiative
Maintains, as well as furthers, and enhances existing machine learning modules for autonomous vehicles, not necessarily the software stack for driving but methods around industrialization of MaaS/TaaS and with that to increase availability of service

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