Research Engineer - Robotics
@ Applied Intuition

Mountain View, California, United States
On Site
Posted 3 days ago

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Job Details

About Applied Intuition

Applied Intuition is a vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Trusted by 18 of the top 20 global automakers, they serve industries including automotive, defense, trucking, construction, mining, and agriculture.

Role Overview

The Research Engineer will join the Research Team to conduct cutting-edge robotics research for autonomous driving and general robotics applications. This role leverages large-scale data, industry-leading simulators, and tools to drive innovation.

Responsibilities

  • Conduct research on robotic foundation models and reinforcement learning.
  • Collaborate with research scientists and interns on top-tier publications.
  • Set up hardware/software for various robots and data equipment.
  • Deploy improvements that directly aid customer programs.

Qualifications

Proven hands-on experience in robotics hardware, data collection, and teleoperation is required. Advanced degrees (MSc/PhD) and a strong record of research publications are highly valued.

Compensation & Benefits

The overall package includes a competitive base salary ($158,000 - $304,000 USD annually), equity, and a comprehensive benefits program including healthcare, retirement benefits, learning and wellness stipends, and paid time off.

Work Arrangement

This is primarily an in-office role based on the Applied Intuition office, with flexibility for occasional remote work to accommodate personal commitments.

How to Get Hired at Applied Intuition

🎯 Tips for Getting Hired

  • Research Applied Intuition's culture: Understand their mission and latest projects.
  • Tailor your resume: Highlight robotics and AI research experience.
  • Prepare technical portfolio: Showcase autonomous systems and hardware skills.
  • Practice interview fundamentals: Be ready for technical and setup questions.

📝 Interview Preparation Advice

Technical Preparation

Review robotics simulation toolkits and datasets.
Practice hardware setup and teleoperation techniques.
Study reinforcement learning and motion control algorithms.
Revisit research publications on autonomous systems.

Behavioral Questions

Explain teamwork in research projects.
Describe challenge handling in complex setups.
Discuss collaboration with multidisciplinary teams.
Share conflict resolution experiences in projects.

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