Senior AI ML Ops Engineer - Must have Autonomous Driving Experience Senior AI ML Ops Engineer - Must have Autonomous Driving Experience Senior AI ML Ops Engineer - Must have Autonomous Driving Experience

Volkswagen AG•Belmont, CA

14d

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. ADMT represents the Volkswagen Group as its driver for building self-driving technology. With experienced leaders in the field and collaborative partnerships with some of the world’s largest automakers, we’re building self-driving technology that is engineered to scale globally and transform mobility for millions. Talented individuals join our team because they share our purpose to make it safe, easy, and enjoyable for everyone to get around. We aspire to impact key industries that move people and goods, from ride hailing to deliveries. Senior Artificial Intelligence MLOps Engineer - MUST HAVE Autonomous Driving experience Role Summary: The 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. This specific role has the main focus areas: To develop reference processes, methods and tools needed to enable, scale, and industrialize MaaS/TaaS applications, including simulation, data analytics, scene understanding, as well as core SDS tasks. To implement those and define KPI to evaluate and benchmark these enablers for autonomous driving To conduct benchmarks and assessments To collaborate with internal and external partners

Requirements

Must have experience with algorithm development for Autonomous Driving tasks including Perception, Sensor Fusion, Motion Prediction, Path Planning, End-to-End Driving, Simulation, Data Analytics, and Artificial Intelligence (AI) technologies & technical 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 hands-on experience in building and deploying models on both on-premises compute and cloud compute (e.g., AWS).
Experience with feature extraction and engineering from camera, lidar, radar, GPS/ D-GPS and HD maps, object-lists, large-scale fleet data, live data and offline data.
Excellent knowledge and practical experience with simulation frameworks such as VTD, Unity, Unreal, ASM or similar.
Experience with software-in-the-loop testing, and good knowledge of hardware-in-the-loop testing.
Experience with data analytics, data-lake modeling, data preparation and quality assessment, building training/validation data pipelines from data lakes to AI models.
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, RNNs, LLMs, LSTMs, GNNs, Foundation Models.
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++, LaTex, Bash, Cmake, Git, Linux, familiar with data structures and algorithms, machine learning and math
Experience with common applied AI and software development tools/libraries: Kubernetes, AWS Sagemaker, Docker, HuggingFace, Weights & Biases, OpenCV, OpenGL, TensorRT, CUDA, Open3D, PCL
7+ years post-grad professional work experience
Master’s degree in computer science or equivalent

Nice To Haves

Experience with current state-of-the-art AI technologies such as Vision-Language Models, Neural Radiance Fields, Agentic AI, Embodied AI, Generative AI, Deep Sensor Fusion
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.
Good knowledge of scenario-based testing, and test design for the validation of autonomous vehicles.
Experience with AD specialized tooling, datatypes, and workflows: DSPACE, OpenScenario, SOTIF, OpenDRIVE, ROS
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.
PhD strongly preferred

Responsibilities

Build scalable AI and ML based solutions to support production AD development use cases including simulation, data analytics, perception, behavior modeling, scene understanding, and fleet operations.
Designs and implements new machine learning based approaches based on existing frameworks
Keeps up to speed with the state of the art of academic research and technology in the industry
Tests developed solutions in simulated, prototype, and real-world vehicles (virtual testing, unit tests, integration tests, in-vehicle/field tests, etc.)
Analyzes and evaluates conducted tests
Presents project/progress reports and presentations to top management, mentors, partners, and project affiliates
Transfers technologies and solutions to ADMT GmbH, CARIAD
Develop KPI and operations frameworks for continuous validation and MLOps.
Build CI/CD AI deployment pipelines to serve models to production teams
Manages and coordinates the tech scouting process
Communicates regularly and influences partners in US and Germany to define, implement, and deliver new applied AI solutions to satisfy production needs.
Expands research network between ADMT LLC and local entities
Manage resource allocation, budget, timelines, and deliverables for work packages.
Initiates and implements partnerships with external partners (companies, research institutions, universities) within Silicon Valley and US
Transfers project outcomes to internal Volkswagen Group partners (ADMT GmbH, CARIAD)
Secures intellectual property