Senior Machine Learning Engineer - Foundation Model

Key Responsibilities

• Design and implementlarge-scale multi-modal architectures (e.g., vision–language–action transformers) for end-to-end autonomous driving.
• Developpretraining and fine-tuning strategies leveraging massive labeled and unlabeled fleet data (images, video, LiDAR, CAN bus, maps, human driving behaviors, etc.).
• Research and integratecross-modal alignment (e.g., visual grounding, temporal reasoning, policy distillation, imitation and reinforcement learning) to improve model interpretability and action quality.
• Collaborate with infrastructure engineers toscale training across thousands of GPUs using distributed training frameworks (FSDP, DDP, etc.).
• Conductsystematic ablation, evaluation, and visualization of model behavior across perception, reasoning, and planning tasks.
• Contribute tomodel deploymentoptimization, including quantization, export, and latency–accuracy trade-offs for onboard execution.

Minimum Qualifications

• Master’s degree or higher inComputer Science, Electrical/Computer Engineering, or related field, with3+ years of experience in deep learning research or productization.
• Strong proficiency inPyTorch and modern transformer-based model design.
• Experience inlarge-scale pretraining ormulti-modal modeling (vision, language, or planning).
• Deep understanding ofrepresentation learning, temporal modeling, andself-supervised orreinforcement learning techniques.
• Familiarity withdistributed training (DDP, FSDP) and large-batch optimization.

Preferred Qualifications

• PhD inCS/CE/EE or related field, with 1+ years of relevant industry experience.
• Publication record in top-tier AI conferences (CVPR, ICCV, NeurIPS, ICLR, ICML, ECCV).
• Prior experience buildingfoundation or end-to-end driving models, orLLM/VLM architectures (e.g., ViT, Flamingo, BEVFormer, RT-2, or GRPO-style policies).
• Familiarity withRLHF/DPO/GRPO,trajectory prediction, orpolicy learning for control tasks.
• Proven ability to collaborate cross-functionally with infra, perception, and planning teams to deliver production-ready models.

• A collaborative, research-driven environment with access to massive real-world data andindustry-scale compute.
• An opportunity to work withtop-tier researchers and engineers advancing the frontier of foundation models for autonomous driving.
• Direct impact on the next generation ofintelligent mobility systems.
• Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
• Competitive compensation package.
• Snacks, lunches, dinners, and fun activities.