5-7 years of experience with modern ML frameworks like PyTorch or JAX
Strong understanding of vision-language models and practical applications
Advanced degree (Master's or PhD) in ML, AI, or Computer Science, or equivalent experience
Ability to write clean, efficient research code with clear reasoning about model behavior
Interest in robotics, controls, or embodied AI
Bonus: Experience with edge-device inference or real-time constraints
Responsibilities
Architect and build training and inference stacks for robotic systems
Design and train new model variants, run experiments, and document results
Propose new research directions to enhance model speed and reliability
Develop fine-tuning and optimization for robotics workloads
Improve throughput in the training and deployment pipeline
Manage datasets and maintain clean data pipelines with the data team
Deploy models to hardware and troubleshoot real-world failures
Benefits
Work in a collaborative, small team environment with senior professionals
Hands-on impact by shipping research directly to deployed systems
In-person work culture for faster project iteration
Opportunity to explore and propose innovative research directions
Access to advanced robotics and AI technology in a cutting-edge company
Full Job Description
About the role
As an AI Researcher at Droyd, you'll own meaningful parts of the learning and inference stack that power our robotic arms. You'll train models, push them onto hardware, and iterate until they work in the real world.
You'll work in person with a small, senior team across robotics, controls, and data. Your work will ship directly to deployed systems.
This role is based in San Francisco, CA. We're an in-person company. We build faster that way. In this role, you'll
Architect and build training and inference stacks for models running on low-payload robotic systems
Design and train new model variants, run experiments, and document results
Propose and explore new research directions that improve speed, reliability, or capability
Develop fine-tuning and optimization methods tailored to robotics workloads
Improve throughput across the full training and deployment pipeline
Work with the data team to manage datasets and keep pipelines clean
Deploy models to hardware and debug real-world failures
We're looking for someone who
Has experience with modern ML frameworks like PyTorch or JAX
Understands vision-language models and how they behave in practice
Holds a Master's, PhD, or equivalent hands-on research experience in ML, AI, or CS
Can ship clean research code and reason clearly about model behavior
Has interest in robotics, controls, or embodied AI
Bonus: experience with edge-device inference or real-time constraints
