Posted 17 days ago

Machine Learning Engineer Intern - Planning

Santa ClaraOn-siteInternship

AI Summary

Designs and researches trajectory prediction models for autonomous trucks, expanding a Scene Transformer framework to generate diverse ego-vehicle trajectories and evaluate long-horizon predictions.

About this role

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.

We’re seeking an enthusiastic and driven Simulation/ML Engineer Intern to join our team. In this role, you’ll help build 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

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.

Skills

AleatoricAutoregressiveAV Stack ComponentsBehavior ForecastingBenchmarkingContrastive LearningEpistemicFailure-mode InvestigationJAXLocalizationLoss Function EngineeringMetrics DesignMulti-agent Motion ModelingMultimodal Architecture DesignMulti-modal PredictionMulti-step LossesPerceptionPlanningProbabilistic ModelingPyTorchPyTorch LightningRecursive LossesRepresentation LearningScene-level ModelingSelf-supervisionTrackingTrajectory PredictionUncertainty Estimation

Machine Learning Engineer Intern - Planning

About this role

Responsibilities:

Required Skills:

Skills

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