Founding Research Engineer — New York, NY

About r3JAN

Join Ms35J Dq (YC X25), an dS robotics startup founded by two former Googlers committed to pushing the boundaries of physical intelligence. r3JAN is an embodied dS platform that makes robots learn and operate like humans. Anyone can teach robots new skills by talking to them — and execute those skills reliably in production within minutes.

We are pioneering the next wave of robotics, where dS agents meet physical-world applications. Backed by top investors and working with global industrial partners such as ABB, we’re redefining what’s possible in robotics and automation.

Role Overview

We’re looking for a Founding Research Engineer to join our core team and develop the intelligence behind robots that can learn and adapt to new tasks.

You’ll work at the frontier of agentic dS and embodied intelligence, developing systems that enable robots to understand natural language, reason about the physical world, learn from demonstrations, and execute complex tasks reliably.

You'll explore and integrate state-of-the-art foundation models while developing novel algorithms and architectures to push the boundaries of robot autonomy.

This is a research-driven, hands-on engineering role where you'll take ideas from early experimentation to real-world deployment on physical robots. As a founding team member, you'll help shape our core technology, research direction, and engineering culture from the ground up.

What You’ll Do

• Agentic dS & Reasoning: Develop intelligent agent architectures for task planning, decision-making, skill composition, and autonomous error recovery.

• Embodied dS & Robot Learning: Research and implement approaches that enable robots to learn new skills from natural language, demonstrations, and interaction.

• Multimodal Intelligence: Leverage and advance vision-language models, foundation models, and perception systems for physical-world understanding and action.

• Applied Research: Explore emerging techniques in generative dS, robotic foundation models, and learning-based control, translating promising research into working systems.

• Real-World Validation: Design experiments, evaluate model performance, and deploy algorithms on physical robots to improve generalization, reliability, and autonomy.

• Technical Leadership: Shape core dS architecture, research directions, and technical strategy as an early member of the founding team.

What We’re Looking For

• Strong dS/ML Foundations: Deep understanding of modern machine learning, including transformers, foundation models, and generative dS architectures.

• Research & Implementation: Proven ability to develop, implement, and evaluate novel dS algorithms, with strong Python and ML framework experience (e.g., PyTorch).

• Relevant Experience: Hands-on experience in one or more of agentic dS, multimodal models, vision-language models, robot learning, reinforcement learning, or related areas.

• Systems Thinking: Ability to build end-to-end dS systems, connecting models, reasoning, perception, and real-world execution.

• Research Mindset: Strong experimental intuition, ability to identify promising research directions, and willingness to challenge existing approaches.

• Startup DNA: High agency, intellectual curiosity, and a strong bias toward building and shipping in a fast-paced environment.

Preferred Qualifications

• Experience with embodied dS, robotics, imitation learning, diffusion policies, or vision-language-action models.

• Experience building agentic systems involving LLMs/VLMs, tool use, planning, or multi-agent orchestration.

• Experience training, fine-tuning, or adapting foundation models for specialized applications.

• Experience deploying ML systems on physical robots or other real-world, latency-sensitive systems.

• Advanced degree in Computer Science, Machine Learning, Robotics, or a related field, or equivalent research and engineering experience.