Responsibilities
- Train and fine-tune multi-modal generative models on large-scale datasets, leveraging diffusion-based training and transformer architectures
- Ensure that generated data meets specific requirements for visual plausibility and fidelity to physical laws.
- Work closely with the autonomous driving team to understand their requirements and exploit the generated dataset for training and validating autonomous driving systems.
Qualifications
- Advanced degree (Ph.D.) or significant industry experience in Computer Science, Electrical Engineering, Robotics, or a related field.
- Strong background in machine learning, data science, and advanced programming skills (Python, TensorFlow, PyTorch, etc.)
- Extensive experience with modern generative AI models, particularly diffusion, transformer, or other architectures relevant to text-to-video generation
Preferred Qualifications
- Experience working on autonomous driving projects or related fields, such as robotics or computer vision, is highly valued. Strong background in computer vision, machine learning, or a related field. Experience with large-scale generative models using transformers and diffusion-based training techniques is highly desirable
- Proven problem-solving skills with the ability to analyze complex data problems and develop innovative solutions that drive business outcomes
- Knowledge of physics-based simulations and their application to video generation
- Proven ability to work on complex projects and collaborate with cross-functional teams
Interview Process
- Application Review - Coding Test - 1st Interview - 2nd Interview - Offer
- The process may vary by position and is subject to change
- Schedule and results will be communicated via the email provided in your application
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