AI Engineer - Autonomous Driving AI Engineer - Autonomous Driving AI Engineer - Autonomous Driving

Volkswagen AG•Belmont, CA

4d•$140,000 - $170,000•Onsite

About The Position

As ADMT, we develop and realize fully autonomous mobility and transportation services. Our mission is to make mobility-and transportation-as-a-service safe, accessible and most attractive for society. For that, we cover the entire ground from strategy and business development, software development and end-2-end integration, fleet operations to next-generation self-driving systems. Being the driver in Volkswagen Group initiative for mobility solutions, we’re an integral part of Volkswagen Group's future success.Brief Role DescriptionThe Center of Excellence within the ADMT LLC focuses on applied research and pre-development with the goal to evaluate and/or develop and transfer innovative technology from industries and research institutions into the autonomous driving domain for technology/supplier decisions and to build the strategic base for a further development of a VW Group owned vertical, integrated AD-stack. AI Engineer - This position will sit in Belmont, CA - relocation is required (provided) if you aren't local. Role Summary This role will be tasked with applying machine learning/deep learning to the autonomous driving industry. This role will focus on AI use cases including test automation, simulation, data analytics etc. to support production testing and validation teams. Working in our facility requires a high level of independence and an ability to deal with lots of ambiguity. This position should be held by a Computer Science Engineer, or equivalent, with experience in the development of Software and Software architecture.Role ResponsibilitiesSoftware Development Builds scalable AI and ML based solutions to support production AD development use cases including simulation, test automation, and data analytics. Maintains, as well as furthers, enhances existing machine learning modules. Designs and implements new machine learning based approaches based on existing frameworks. · Develop KPI and operations frameworks for continuous validation and MLOps. Keeps up to speed with the state of the art of academic research and technology in the industry. Transfers technologies and solutions to Volkswagen Group. Software Testing and Evaluation Integrates new software modules into existing cloud, data, and simulation frameworks. Defines and executes test cases based on insights derived from AI data analytics. Tests developed modules in the prototype (unit tests, integration tests, in-vehicle/field tests, etc.). Analyzes and evaluates conducted tests. Assess quality of test environment, AI models, and driving function to identify areas for improvement Process Documentation Develops technical specifications and documentation.

Requirements

5+ years or equivalent.
Master’s Degree in Computer Science or equivalent.
Strong communication skills - ability to explain complex technical topics to non-experts.
Team player with good collaboration and integration skills – joining people, processes and systems.
Highly innovative and capable of seeing problems and potential solutions in a new light.
Able to work in a dynamic, multi-disciplinary, timeline and target oriented work environment.
Problem solving skills.
Analytical skills.
Conceptual thinking skills.
Background in Deep Neural Network Learning, Computer Vision and Machine Learning.
Experience with the complete applied AI/ML development process for a variety of model and problem types: problem definition, architecture definition, training and validation, hyperparameter tuning, cloud deployment and operations, etc.
Strong programming skills with Python and PyTorch/TensorFlow on desktops and distributed cloud backends (e.g. AWS).
Experience with data gathering, data quality, system architecture, coding best practices.
Experience with feature extraction and engineering from camera, lidar, radar, GPS/ D-GPS and HD maps, object-lists, and fleet data lakes.
Excellent knowledge and practical experience with AI technologies for simulation and data analytics for autonomous driving or related fields
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 CNNs, RNNs, LSTMs, LLMs, GNNs, Foundation Models, and the latest research trends.
Knowledge and experience with different ML paradigms such as supervised/unsupervised learning, reinforcement learning, self-supervised learning, and imitation learning paradigms
Specification/Documentation of interfaces between software modules.

Nice To Haves

PhD strongly preferred
Expert knowledge in Software-in-the-Loop testing
Excellent knowledge and practical experience with simulation frameworks such as VTD, Unity, Unreal, ASM, or similar
Excellent knowledge of concepts and methods for the validation of automated driving including scenario-based testing
Experience with algorithm development for simulation and data analytics use cases, including AI digital twins, scene understanding, outlier detection, synthetic data generation, scenario modeling, traffic modeling, neural reconstruction, AI automation, etc.
Graphical Models.
Object Detection, NLP, Scene Understanding.
Background or strong interest in automotive engineering.
Experience with C++, CUDA, OpenCV and MATLAB.
Big Data and cloud experience strongly preferred.
C++ & GPU Programming.
Experience with AD specialized tooling, datatypes, and workflows: DSPACE, OpenScenario, SOTIF, OpenDRIVE, ROS
Experience in regulated industries such as automotive, aerospace, medical devices etc.
Passion for cars or physical products.

Responsibilities

Builds scalable AI and ML based solutions to support production AD development use cases including simulation, test automation, and data analytics.
Maintains, as well as furthers, enhances existing machine learning modules.
Designs and implements new machine learning based approaches based on existing frameworks.
Develop KPI and operations frameworks for continuous validation and MLOps.
Keeps up to speed with the state of the art of academic research and technology in the industry.
Transfers technologies and solutions to Volkswagen Group.
Integrates new software modules into existing cloud, data, and simulation frameworks.
Defines and executes test cases based on insights derived from AI data analytics.
Tests developed modules in the prototype (unit tests, integration tests, in-vehicle/field tests, etc.).
Analyzes and evaluates conducted tests.
Assess quality of test environment, AI models, and driving function to identify areas for improvement
Develops technical specifications and documentation.