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Senior AI Engineer (ML/DL)

LinkedIn Volkswagen of America, Inc Belmont, CA
Mid-Senior level Posted April 5, 2026 Job link
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Requirements
  • To be considered, Candidates MUST have extensive experience in the following: Computer Vision, Deep Learning, forecasting, transformers, CNNs.
  • You must also possess strong experience building data models.
  • Represents Volkswagen Group in the technical community, such as at conferences.
  • Qualification requirements Qualifications • 6 - 8 years of professional experience post graduate degree PREFERRED • 4+ years’ Deep Learning experience post graduate degree PREFERRED Education Requirements: • Master’s Degree in Computer Science or equivalent.
  • Education Desired • PhD Strongly Preferred Required Skills: Deep Learning : Proficiency in deep learning techniques and frameworks Machine Learning : Strong understanding of traditional machine learning algorithms and their applications.
  • Computer Vision : Expertise in computer vision, including object detection, image segmentation, and image recognition Natural Language Processing (NLP) : Proficiency in NLP techniques, including sentiment analysis, text generation, and language understanding models.
  • Experience with multimodal language modeling and applications.
  • Neural Network Architectures: Deep understanding of various neural network architectures such as CNNs, RNNs, and Transformers .
  • Reinforcement Learning: Familiarity with reinforcement learning algorithms and their applications in AI.
  • Data Preprocessing: Skills in data cleaning, feature engineering, and data augmentation.
  • Model Training and Tuning: Experience in training, fine-tuning, and optimizing AI models.
  • Model Deployment: Knowledge of model deployment techniques, including containerization (Docker) and orchestration (Kubernetes).
  • Documentation: Strong documentation skills for model architecture, code, and processes.
  • Desired Skills: AI Ethics: Awareness of ethical considerations in AI, including bias mitigation and fairness.
  • Legal and Regulatory Knowledge: Understanding of AI-related legal and regulatory considerations, including data privacy and intellectual property.
  • Data Management: Proficiency in data storage and management systems, including databases and data lakes.
  • Cloud Computing: Familiarity with cloud platforms like AWS, Azure, or GCP, and their AI services.
  • Work Flexibility • Travel is estimated to be 5-10%, as needed within U.S. and overseas.
Preferred Skills
  • Education Desired • PhD Strongly Preferred Required Skills: Deep Learning : Proficiency in deep learning techniques and frameworks Machine Learning : Strong understanding of traditional machine learning algorithms and their applications.
  • Computer Vision : Expertise in computer vision, including object detection, image segmentation, and image recognition Natural Language Processing (NLP) : Proficiency in NLP techniques, including sentiment analysis, text generation, and language understanding models.
  • Neural Network Architectures: Deep understanding of various neural network architectures such as CNNs, RNNs, and Transformers .
  • Reinforcement Learning: Familiarity with reinforcement learning algorithms and their applications in AI.
  • Data Preprocessing: Skills in data cleaning, feature engineering, and data augmentation.
  • Model Training and Tuning: Experience in training, fine-tuning, and optimizing AI models.
  • Model Deployment: Knowledge of model deployment techniques, including containerization (Docker) and orchestration (Kubernetes).
  • Desired Skills: AI Ethics: Awareness of ethical considerations in AI, including bias mitigation and fairness.
  • Legal and Regulatory Knowledge: Understanding of AI-related legal and regulatory considerations, including data privacy and intellectual property.
  • Data Management: Proficiency in data storage and management systems, including databases and data lakes.
  • Cloud Computing: Familiarity with cloud platforms like AWS, Azure, or GCP, and their AI services.
Education
  • (Not required) – Qualification requirements Qualifications • 6 - 8 years of professional experience post graduate degree PREFERRED • 4+ years’ Deep Learning experience post graduate degree PREFERRED Education Requirements: • Master’s Degree in Computer Science or equivalent.
  • (Required) – Education Desired • PhD Strongly Preferred Required Skills: Deep Learning : Proficiency in deep learning techniques and frameworks Machine Learning : Strong understanding of traditional machine learning algorithms and their applications.