Chief Science Officer (m/f/d)

Location: Hybrid; Zurich or Stuttgart, with Boston possible. Relocation support is available.

Company

hirify.global is a Stuttgart-founded robotics company and frontier research lab building Cortex, a hardware-agnostic vision-language-action foundation model for robots operating in live warehouse production across Europe and the US.

What you will do

• Set the research agenda for Cortex across vision-language-action models, world models, planning, learning from interaction on real robots, and generalization across tasks and embodiments.
• Make research investment decisions across people and compute, including deciding which directions to pursue or stop.
• Own the data strategy, including deployment, teleoperation, open-source, synthetic data, and future fleet data collection.
• Own the compute strategy from large-scale training through real-time robot inference, and build evaluation benchmarks that predict customer-operation performance.
• Build and lead the research organisation in Zurich and Stuttgart, including its structure, research leads, hiring bar, and operating rhythm.
• Take research into production with engineering, define publication, open-source, and patent decisions, and represent hirify.global with customers, partners, universities, and investors.

Requirements

• Experience leading research in robot learning or embodied AI, including VLA models, imitation learning, or reinforcement learning, and building a team around it.
• Experience running research on real robots, ideally outside the lab and for extended periods.
• Strong scientific standing, including a record at top research venues and a network of researchers.
• Experience making decisions on research bets, data, and compute, including stopping initiatives that did not work.
• Ability to explain science to engineers, customers, and investors.
• PhD in machine learning, robotics, or a related field, or an equivalent track record.
• Ability to partner with the CTO, product, and operations so research, engineering, and deployment align.

Nice to have

• Large-scale pretraining of foundation models.
• Fleet learning or data-engine development.
• Industrial manipulation experience.
• Experience in both academia and industry.

Culture & Benefits

• Small, senior teams with a flat structure where execution counts more than titles.
• Robots operating in live production and generating continuous real-world learning data.
• Leadership-team position in a company scaling from Europe into the US, with meaningful equity.
• Large-scale compute and the freedom to build the desired research organisation.
• Teams in Stuttgart, Zurich, and Boston, with relocation support.

Hiring process

• Conversations with both founders.
• Research deep dive with the team.
• Working session on a real deployment problem.