Member of Technical Staff; MTS - Multimodal Foundation Models Job Arvada area,Colorado USA,Business

Position: Member of Technical Staff (MTS) - Multimodal Foundation Models

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

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

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