Senior Machine Learning Engineer - Foundation Model

Design and implement large-scale multi-modal architectures (e.g., vision–language–action transformers) for end-to-end autonomous driving.

Develop pretraining and fine-tuning strategies leveraging massive labeled and unlabeled fleet data (images, video, LiDAR, CAN bus, maps, human driving behaviors, etc.).

Research and integrate cross-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 to scale training across thousands of GPUs using distributed training frameworks (FSDP, DDP, etc.).

Conduct systematic ablation, evaluation, and visualization of model behavior across perception, reasoning, and planning tasks.

Contribute to model deployment optimization, including quantization, export, and latency–accuracy trade-offs for onboard execution.

Master’s degree or higher in Computer Science, Electrical/Computer Engineering, or related field, with 3+ years of experience in deep learning research or productization.

Strong proficiency in PyTorch and modern transformer-based model design.

Experience in large-scale pretraining or multi-modal modeling (vision, language, or planning).

Deep understanding of representation learning, temporal modeling, and self-supervised or reinforcement learning techniques.

Familiarity with distributed training (DDP, FSDP) and large-batch optimization.

PhD in CS/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 building foundation or end-to-end driving models, or LLM /VLM architectures (e.g., ViT, Flamingo, BEVFormer, RT-2, or GRPO-style policies).

Familiarity with RLHF/DPO/GRPO, trajectory prediction, or policy 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 and industry-scale compute.

An opportunity to work with top-tier researchers and engineers advancing the frontier of foundation models for autonomous driving.

Direct impact on the next generation of intelligent 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.