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Research Scientist - Multimodal Representation Learning

Job in Centennial, Arapahoe County, Colorado, USA
Listing for: Dormont Manufacturing Co
Full Time position
Listed on 2026-07-24
Job specializations:
  • IT/Tech
    AI Business & Operations, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 130000 USD Yearly USD 90000.00 130000.00 YEAR
Job Description & How to Apply Below

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.

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
  • Requirements Core 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
  • Preferred Qualifications
  • Publications in top-tier venues:
    • CVPR
    • ICCV
    • NeurIPS
    • ICLR
  • Experience training models at scale using:
    • Deep Speed / Megatron-LM
  • Strong intuition for why models behave the way they do , not just how to train them
  • #J-18808-Ljbffr
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