Research Intern (AI Robotics)

Location: Mountain View, United States

Company

hirify.global develops generalist intelligent robots across the full robotics stack, including hardware, robot systems, foundation world models, infrastructure, and manufacturing.

What you will do

• Contribute directly to a major ongoing research and engineering project for generalist robotics.
• Work on project-specific problems involving large-scale video-based robot policy learning, multimodal/VLM architectures, simulation, SLAM, navigation, or related robotics systems.
• Train and debug large deep-learning models and develop production-quality research code.
• Collaborate closely with an assigned mentor and the broader research team.

Requirements

• Currently pursuing or recently completed a PhD in Computer Science, Robotics, Machine Learning, or a related field; being close to graduation is preferred. Strong Master’s or Bachelor’s candidates with equivalent research experience may also be considered.
• Strong foundation in deep learning, including hands-on experience training and debugging large models.
• Solid software engineering skills and ability to write production-quality research code rather than only notebooks.
• Experience with one or more of video or generative models, VLMs or multimodal architectures, robot learning, simulation environments such as MuJoCo, Isaac Sim, or Habitat, or SLAM/navigation.
• Track record of independent research.
• Comfort working in a fast-moving, resource-constrained startup research environment.

Nice to have

• Research publications, especially for candidates focused on applied or major-project work.

Culture & Benefits

• Full-time internship with direct collaboration with an assigned mentor from day one, including regular guidance and feedback.
• Access to compute resources scoped to the project.
• Work on problems connected to a real generalist-robotics product rather than a standalone research exercise.
• Potential full-time offer at the end of the internship based on the internship evaluation.

Hiring process

• Structured interview process covering domain knowledge and coding.
• Mid-internship check-in and end-of-internship evaluation, with the latter able to lead to a full-time offer.