Research Scientist - Multimodal Representation Learning

Deeproute.ai • Fremont, CA

8h

About The Position

We are looking for a research scientist to push the frontier of multimodal representation learning for autonomous driving. You will focus on method-level innovation, including designing new learning paradigms, architectures, and training strategies for large-scale vision and video models. This role is ideal for candidates who care deeply about how models learn, not just how to train them.

Requirements

• Strong academic background in Computer Science, AI, or related fields
• Solid understanding of modern representation learning frameworks: CLIP, DINOv2, Masked Autoencoders
• Proven experience in method-level innovation, such as: Designing new loss functions, Modifying architectures, Creating new training strategies

Nice To Haves

• Publications in top-tier venues: CVPR, ICCV, NeurIPS, ICLR
• Experience training models at scale using: DeepSpeed / Megatron-LM
• Strong intuition for why models behave the way they do, not just how to train them

Responsibilities

• Design and develop novel representation learning methods, including: Self-supervised learning, Contrastive learning, Masked modeling, Teacher-student / distillation frameworks
• Innovate on model architectures, including: Vision Transformers (ViT), Video models (e.g., Video Swin), Multimodal fusion architectures
• Develop new training paradigms and loss functions to improve representation quality
• Drive measurable improvements in: Representation quality (e.g., linear probe, retrieval metrics), Downstream performance (e.g., perception / E2E driving systems)
• Collaborate with engineering and data teams to integrate new methods into production systems

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 11-50 employees