Applied Scientist - Agents & Robotics

RAI Institute; Zürich; On-site; CHF 90,000 - 130,000; Full time

Job summary

RAI Institute is seeking highly motivated Master's and PhD graduates to join our team full-time in an invigorating environment where researchers and engineers are building the future of robotics and learning-based systems.

You will focus on developing and scaling agentic infrastructure for robot autonomy, working with engineers and researchers to integrate with powerful simulations and on-robot deployments, and ensuring production-grade reliability in Linux environments.

Qualifications

• MS or PhD in robotics, computer science, computational science & engineering or related field.
• Proven software engineering experience (internships, open-source contributions, or project work).
• AI/ML foundations: PyTorch and understanding of modern AI architectures (LLMs, VLMs, RL).

Responsibilities

• Build, extend, and maintain an agentic framework for on-robot workflows across real-world deployments.
• Create and manage internal benchmarks for evaluating agentic workflows in diverse robotic tasks.
• Collaborate with engineers and researchers to integrate with simulation tools and on-robot deployments.
• Profile, benchmark, and optimize performance in resource-constrained Linux environments for production reliability.

Skills

Software engineering

PyTorch

AI architectures

Education

Master's or PhD in Robotics/CS/Computational Science & Engineering

Tools

ROS2

Isaac Sim

MuJoCo

Job description

Our Mission

Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives.

Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives. We are looking for highly motivated Master's and PhD graduates to join our team full-time in an invigorating environment where researchers and engineers are building the future of robotics and learning-based systems. Strong candidates will bring exceptional talent with solid fundamentals in agents and system design. In this role, you will focus on developing and scaling agentic infrastructure and systems for robot autonomy. If you have a passion for robots and a desire to be part of the advancement of robot capabilities and usefulness, you will want to join us!

What You'll Do

• Build, extend, and maintain an agentic framework for managing on-robot workflows across various real-world deployment scenarios.


• Create and manage internal benchmarks for the comprehensive evaluation of agentic workflows in diverse robotic tasks.


• Work closely with engineers and researchers to integrate your work with powerful simulation tools and on-robot deployments.


• Profile, benchmark, and eliminate performance bottlenecks in resource-constrained Linux environments to ensure production-grade reliability.

What You'll Need

• A completed Master's (MS) or PhD degree in Robotics, Computer Science, Computational Science & Engineering, or a related field.


• Proven software engineering experience (e.g., industry internships, significant open-source contributions, or complex academic/industry project work).


• AI/ML Foundations: Experience with PyTorch and a strong understanding of modern AI architectures (LLMs, VLMs, or Reinforcement Learning).

Bonus

While strong core software engineering fundamentals in systems programming are required, no specific domain expertise beyond that is necessary. However, if you happen to possess experience in any single one of the following areas, it would be a massive plus and highly relevant to our current projects:

• Sim-to-Real Experience: Experience in deploying ML workflows on physical hardware.


• Vision-Language Models (VLMs): Experience integrating multimodal models for robotic perception and task planning.


• Simulators: Experience testing code in simulated environments (e.g., Isaac Sim, MuJoCo).


• Robotic Middleware: Familiarity with ROS2.


• Robotic Perception: Familiarity with various scene representations (e.g., Gaussian Splattings, Scene Graphs, World Models, SDFs, etc.), perception frontends (e.g., DINO, SAM, SiGLIP, etc.), and approaches to scene understanding.


• Robot Learning: Experience in training ML models for robot action policies, robot perception frontends, and state estimation.

We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.