Automated Driving Advanced Development Intern, Machine Learning Research

Tri-global Solutions Group Inc.

. Conduct research advancing generative modeling for end-to-end vision-based planning in automated driving .

Posted 11/4/2026internshipLos Altos • California • United StatesEntry Level💰 $45 - $65 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in generative modeling and machine learning for automated driving applications, with proficiency in Python and experience in ML frameworks like PyTorch. Capable of implementing and evaluating complex architectures, conducting simulations, and collaborating effectively within interdisciplinary teams.

Highest-signal resume keywords

Ph.D. In Computer Science, Robotics, Engineering, Or Related FieldProficiency In PythonExperience With ML Frameworks Such As PyTorchHands-On Experience With Robotics Or Real-World Sensor DataExperience Working With ROS And Simulation Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative ModelingMachine Learning Engineering WorkflowsModel TrainingTrajectory OptimizationObject Detection3D PerceptionTransfer LearningImitation LearningDebugging On NVIDIA CUDA StackExperiment Tracking

Soft Skills

CollaborationProblem-Solving

Tools & Technologies

Weights & BiasesMLflowMetaflowCARLANvidia DriveSim

Industry Keywords

Automated DrivingEnd-To-End Vision-Based PlanningSensor SimulationsMultimodal ModelsVehicle Trajectories

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Conduct research advancing generative modeling for end-to-end vision-based planning in automated driving
Implement scalable end-to-end architectures processing raw sensor data to generate vehicle trajectories
Address long-tail driving scenarios with low data coverage
Prototype, validate, and iterate on model architectures using imitation learning and large-scale data
Perform closed-loop evaluations in sensor simulations and real-world testing environments
Explore multimodal and language-conditioned models using external data sources and transfer learning
Implement, evaluate, and integrate ML-based components for perception, planning, and control
Conduct simulation-based testing
Collaborate with researchers, data engineers, and autonomy engineers to scale models from prototype to production
Contribute to Toyota’s global AI efforts and end-to-end learned driving stack project with Woven by Toyota

Requirements

What you’ll need

Currently pursuing a Ph.D. or equivalent experience in Computer Science, Robotics, Engineering, or a related field
Proficiency in Python for implementing and evaluating research ideas
Experience with ML frameworks such as PyTorch
Understanding of version control, testing, and software engineering fundamentals
Experience in ML engineering workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization
Understanding of debugging and profiling on NVIDIA CUDA stack
Hands-on experience with metrics dashboards, experiment tracking, and ML ops tooling such as Weights & Biases, MLflow, or Metaflow
Hands-on experience working with robotics or real-world sensor data, such as video, lidar, IMU, or radar
Experience in state-of-the-art architectures for object detection and 3D perception
Familiarity with foundation models, pre-training and efficient fine-tuning, multimodal Transformer architectures, and large-scale distributed training
Experience working with ROS, simulation frameworks such as CARLA or Nvidia DriveSim, or vehicle interfaces
Experience with robot motion planning techniques such as trajectory optimization, sampling-based planning, or model predictive control, or automated driving domains

Benefits

Comp & perks

Paid 12-week internship
Medical insurance
Dental insurance
Vision insurance
Paid time off, including holiday pay and sick time