PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World's Most Innovative Companies. Partners including TRATON GROUP's Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you're ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
In this role, the intern will expand the scene transformer model to provide multiple trajectories for ego in ambiguous cases, and explore longer horizon predictions using recursive and multi-step losses.
Area of work:
Deep Learning Models, Planning, Prediction
Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.
Responsibilities::
• Multimodal Architecture Design: Modify and expand an existing Scene Transformer framework to generate a diverse set of ego-vehicle trajectories for ambiguous scenarios.
• Loss Function Engineering: Formulate and experiment with recursive, autoregressive, and multi-step losses to stabilize long-horizon trajectory rollouts.
• Diversity & Feasibility Optimization: Mitigate mode collapse to ensure the generated paths are distinctly varied yet kinematically feasible.
• Evaluation & Benchmarking: Design metrics to evaluate trajectory diversity, safety, and long-horizon accuracy against real-world driving logs.
Required Skills::
• Expertise in trajectory prediction, behavior forecasting, and multi-agent motion modeling
• Experience training large-scale models with self-supervision, contrastive learning, representation learning, or scene-level modeling
• Practical experience with PyTorch, PyTorch Lightning or JAX.
• Experience with uncertainty estimation (aleatoric, epistemic), multi-modal prediction, and probabilistic modeling
• Understanding of AV stack components: localization, perception, tracking, prediction, and planning.
• Strong debugging, experiment design, data analysis, and failure-mode investigation skills.