Applied Researcher

Aurora InnovationSeattle, WA

About The Position

Aurora's mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn. Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a a PhD to serve as our technical pathfinder in the realm of Vision-Language-Action (VLA) models. You won't just be applying existing tech; you will be identifying the 'jagged edges'—the points of failure in current state-of-the-art models—and helping us rediscover and rebuild our architecture from the ground up. In this role, you will focus on Architectural Exploration: Deep dive into VLM/VLA architectures to determine their viability for our specific problem sets. Technical Mentorship: Act as the subject matter expert and guide for an exceptionally capable engineering team eager to move into this space. Practical Implementation: Bridge the gap between high-level academic theory and practical, scalable applications. Innovation: Redesign and optimize model architectures to leverage high-performance computing environments like Aurora.

Requirements

  • PhD Graduate in AI, Computer Science, or Robotics (Top-tier research lab background)
  • Deep expertise in Vision-Language Models (VLM) and Vision-Language-Action (VLA) models
  • Hands-on experience with 'jagged edges'—knowing where current architectures fail and how to troubleshoot them
  • Practical researcher: Ability to translate complex papers into production-ready code
  • Collaborative Guide: Willingness to mentor existing team members and bridge the knowledge gap
  • Excitement for large-scale infrastructure and supercomputing environments (e.g., Aurora)
  • Architectural Creativity: Ability to rethink and redo entire model architectures rather than just fine-tuning
  • Strong programming skills in Python
  • Strong depth programming in modern C++

Responsibilities

  • Deep dive into VLM/VLA architectures to determine their viability for our specific problem sets.
  • Act as the subject matter expert and guide for an exceptionally capable engineering team eager to move into this space.
  • Bridge the gap between high-level academic theory and practical, scalable applications.
  • Redesign and optimize model architectures to leverage high-performance computing environments like Aurora.
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