We’re seeking an enthusiastic and driven Simulation/ML Engineer Intern to join our team and work on an exciting project that blends Large Language Models (LLMs) with simulation technology. In this role, you’ll help develop a tool that can generate realistic, scalable simulation scenarios from text and real road data. This is a fantastic opportunity to apply your machine learning and robotics knowledge to real-world challenges, while working on a project that will revolutionize how simulation scenarios are created, with minimal manual effort. You’ll be at the forefront of innovation, helping us expand our capabilities in testing autonomous vehicles using large-scale simulation with LLM-driven solutions.
Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience.
Responsibilities:
Gain a strong understanding of our simulation systems and data infrastructureDevelop machine learning models to generate realistic simulation scenarios from text, images and other types of recorded dataCollaborate with the simulation teams to refine and optimize the generated scenariosTest and improve model performance based on ground truth dataContribute to integrating the tool into existing simulation workflows,
Required Skills:
Currently pursuing or recently graduated with a degree in Computer Science, Robotics, Machine Learning, AI, or a related field1+ years of experience in machine learning (Deep Learning, NLP, etc.)Experience with simulation frameworks (e.g., Gazebo, V-REP, Unity) and robotics applicationsStrong programming skills in Python and familiarity with machine learning libraries (TensorFlow, PyTorch, etc.),
Preferred Skills:
Experience working with Large Language Models (LLMs) and multimodal learning (text + images)Familiarity with scenario generation and counterfactual simulation techniquesKnowledge of text-to-image generation and data preparation for machine learning in simulation environments