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Salary
≈ $138k – $264k per year (Estimated)
Location
In office (San Francisco)
Seniority
Middle · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Jun 8, 2026. Mimic Robotics scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Mimic Robotics is a physical AI company building general-purpose dexterous manipulation, with robotic hands trained by imitating human demonstrations and in-house hand hardware. Founded in 2024 by ETH Zurich researchers, it targets repetitive manual tasks in light manufacturing and hires electrical, mechanical and AI research engineers. The company is headquartered in Zurich, Switzerland.
Backed by Speedinvest

At mimic we are a frontier physical AI company pioneering general-purpose dexterous manipulation across the entire stack.

Spun out of ETH Zurich research in 2024, our team develops both state-of-the-art Video-Action Models and custom, in-house robotic hand hardware. Our growing team brings together world-class researchers working across our offices in Zurich and San Francisco.

As an AI Research Engineer (Robot Learning) you will drive frontier AI model development and data flywheel project management for dexterous robotic manipulation. You will shape all aspects of the development of end-to-end AI models for robotics, from large scale multi-task pre-training to specialized fine-tuning and post-training. You will also be responsible for the implementation and management of the data flywheel process, supervising and organizing task specification, data collection, model training and model evaluation in the real world. As an early employee, you will immediately co-lead AI engineering and science in close contact with the founders and early team.

Responsibilities

  • Drive research and implementation for large scale, multi-task foundation AI models for robotics, quickly iterate over architecture design and parameters
  • Oversee model specialization for end use cases with fine-tuning and other post-training techniques
  • Drive the implementation and management of the data flywheel process, from data specification, to data collection, model training and real world evals
  • Write clean, maintainable python code using deep learning frameworks
  • Work closely with the Robotics and Hardware teams to ensure efficient and stable deployment on real world robots

Requirements

  • PhD in Computer Science, Data Science, Robotics or related field, or equivalent PhD-level experience in industry
  • 3+ years of experience training generative models
  • 4+ years of experience with developing and maintaining Python code
  • Strong empirical research abilities and intuitions
  • Project management / supervision experience
  • Fluent English speaker

Nice to have

  • Published deep learning and/or robot learning research in leading conferences (NeurIPS, CoRL, ICML, ICLR, etc.)
  • Experience in training large scale foundation models with distributed multi-GPU setups
  • Robotics and ROS2 experience
  • Experience with RL fine-tuning of generative models
  • Experience in open source software development

Compensation & Benefits

  • We offer a total compensation package including a competitive yearly base salary and a strong stock option package to make you part of our shared success.
  • You will work with the founders from day one, shaping the company and participating in its success from its early stages.
  • Surprise team trips, free gym and sports subscription, joint breakfasts and dinners and other exciting team activities.

You will have the opportunity to shape a robotics & AI company from the ground up. In flat hierarchies you will work directly with the founders and some of the best talents in the robotics space from the likes of Google DeepMind, Tesla Optimus, Stanford, ETH, ABB, etc. At mimic, you are accepted for who you are. As part of our ongoing journey towards creating a diverse and inclusive environment we encourage everyone to apply and we are looking forward to you bringing along your knowledge, personal experiences, and fresh perspectives. Together we can solve some of the greatest challenges in robotics.

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