Senior Engineer - Perception Modeling

On our Perception team, you have the opportunity to work with world-class ML engineers and research scientists, whose mission is to make self-driving vehicles a reality and to create a positive social impact. Our team works on the tech stack responsible for perceiving the dynamic scenarios, and further tracking and classifying objects around our robo-taxi. We are looking for engineers who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You'll Be Doing:

• Lead the architecture and development of advanced perception systems, focusing on, large-scale multi-modal foundation models, and robust knowledge generalization across vehicle generations
• Architect and scale synthetic data generation and sensor simulation capabilities to tackle long-tail edge cases, unseen off-log scenarios, and closed-loop evaluation
• Drive knowledge transfer from large teacher/foundation models to efficient onboard real-time perception models via advanced distillation and post-training techniques
• Productionize and deploy solutions onto autonomous vehicle fleets
• Provide technical leadership, mentorship, and guidance to senior and mid-level engineers on the team

What We're Looking For:

• 3+ years of experience in Machine Learning, Computer Science, Robotics, or a related field
• Masters or Ph.D. in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience
• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience with designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, multi-object tracking, and/or end-to-end perception
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries and Python bindings development experience
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
• Excellent communication and interpersonal skills
• Experience mentoring and leading others

Preferred, but not required:

• Proven track record in designing, training, or fine-tuning Foundation Models (e.g., Vision-Language Models, Multimodal Transformers) for autonomous driving or robotic perception
• Deep expertise in World Models, generative video/lidar prediction, scene synthesis, and sensor simulation for closed-loop evaluation
• Strong experience with Knowledge Distillation and model compression techniques to transfer capability from large offline teacher models to lightweight edge deployments
• Demonstrated experience with Synthetic Data Generation (SDG) and multi-modal automated labeling systems to scale training data quality and volume
• Publications in premier computer vision or machine learning conferences (e.g., CVPR, ICML, NeurIPS, ICCV, ECCV)

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