Lead research and implementation of large-scale, multi-task foundation models for dexterous robotic manipulation; manage the data flywheel from specification through collection, training, and real-world evaluation; fine-tune and specialize models; write maintainable Python deep-learning code; and collaborate with Robotics and Hardware teams to deploy models on real robots while co-leading AI engineering efforts.
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.
Similar Jobs
Automotive
Designs, builds, maintains, and evolves Informatica IDMC and MDM SaaS solutions, integrations, dataflows, and business-critical software. Integrates systems using API- and event-based GCP patterns, Java, and Spring Boot. Leads requirements breakdown, guides projects through deployment, applies automated testing and CI/CD, documents architectures, mentors teammates, and advances AI-assisted development practices.
Top Skills:
BpelC4 ModelingCi/CdCloud App Integration (Cai)Cloud Data Integration (Cdi)Cloud Data Quality (Cdq)Customer 360 MdmData Integration & ReplicationETLGCPGitInformatica IdmcInformatica Mdm SaasJavaJIRAJSONMermaidNoSQLSafeSpring BootSQLXpathXquery
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Owns technical product capabilities for ServiceNow University’s AI-native learning and credentialing experiences. Defines strategy, roadmaps, requirements, reusable platform capabilities, integration patterns, and measurable outcomes. Partners with Engineering, Architecture, Design, Research, Data, and platform teams to deliver scalable, secure, accessible, and enterprise-ready experiences involving personalization, conversational interfaces, learner data, search, recommendations, and AI technologies.
Top Skills:
Ai AgentsAPIsArtificial IntelligenceCloud TechnologiesConversational SystemsDistributed SystemsLarge Language ModelsLuxPersonalizationRecommendationsSearchServicenow
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Own enterprise-level corporate strategy workstreams from problem framing through recommendation. Build market, competitive, customer, financial, and internal analyses; develop strategic narratives; and present findings to the CFO, executive leadership team, and Board. Partner with business unit leaders, Corporate Development, and Ventures on market strategy and inorganic opportunities.
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


