AI/Machine Learning Fellowship, 6-12 Months

Volkswagen Group

. Apply machine learning to automotive applications including autonomous driving, manufacturing, and material design .

Posted 11/5/2026full-timeBelmont • California • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning applications for automotive technologies, particularly in developing AI solutions, data processing methods, and neural network architectures. Proficient in Python programming and deep learning frameworks, with a strong foundation in image processing and data quality management.

Highest-signal resume keywords

Python ProgrammingDeep Learning FrameworksData Processing MethodsNeural Network ArchitecturesImage Processing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData GatheringData QualitySystem ArchitectureTransformersCNNsRNNsLSTMsObject DetectionNLP

Soft Skills

Independent WorkInitiativeTeam CollaborationMotivationQuick Learning

Tools & Technologies

LinuxTensorFlowPyTorch

Industry Keywords

Automotive ApplicationsAutonomous DrivingSensor Data ProcessingNeural Network ModelsEnvironmental Perception

Tech Stack

Tools & technologies

LinuxPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Apply machine learning to automotive applications including autonomous driving, manufacturing, and material design
Develop state-of-the-art AI solutions using machine learning techniques on large datasets
Develop modern sensor-data-processing methods to enable safe and robust automated driving
Support AI researchers and engineers in identifying suitable learning methods for robust perception
Pre-process driving data, including checking labels and formatting
Support project teams in building data pipelines for training deep neural networks
Benchmark and report the performance of neural network models
Research network architectures for time-series prediction and anomaly detection
Research network architectures to improve environmental perception using optical sensors
Research supervised and unsupervised learning methods to estimate road participants’ depth, motion, and velocity
Research neural networks for camera-image interpretation, including object detection, panoptic segmentation, and trajectory/motion planning
Fuse neural networks to reduce memory and computational requirements

Requirements

What you’ll need

Six-month minimum commitment
Masters or PhD candidates only
Must be currently enrolled at an accredited University/College in a Masters or PhD program, or graduation date must be within the last six months
Must have a cumulative GPA of at least 3.0
Strong Python programming skills
Good experience using Linux
Experience with deep learning frameworks such as TensorFlow and PyTorch
Good knowledge of image processing and machine learning
Ability to work independently, show initiative and motivation, and work in a team
Experience with data gathering, data quality, system architecture, and coding best practices
Ability to launch projects, quickly learn, and develop ideas in an interdisciplinary environment
Experience extracting high-level logical structure from low-level, multi-dimensional data
Experience with Transformers, CNNs, RNNs, LSTMs, and the latest research trends
Knowledge of graphical models
Knowledge of object detection, NLP, and scene understanding
Passion for cars or physical products
International Students/OPT or CPT cannot be considered at this time

Benefits

Comp & perks

Full-time employment
Fixed-term fellowship of 6–12 months
Up to 40% remote working