Team Lead Machine Learning

Hexagon Robotics; Zürich; Hybrid; CHF 140,000 - 200,000; Full time

Benefits offered by this job

CHF 500 mobility credit for commuting

Bonus system

Strong pension contributions

Relocation support

Health discounts

Team events

Flat hierarchy

International culture

Job summary

Hexagon Robotics is seeking a Team Lead Machine Learning, Physical AI in Zürich to guide a leaderless, hands-on ML team focused on turning human demonstrations into reliable robotic manipulation policies. You will own data collection, training, and deployment loops while mentoring engineers and researchers across the stack.

The role blends leadership with technical depth in imitation learning and visuomotor control, operating in a hybrid setup with close collaboration across R&D, product, and

Qualifications

• PhD or MSc or equivalent in a relevant field,
• Demonstrated leadership of ML teams and projects,
• Strong Python and PyTorch skills with production experience,

Responsibilities

• Build and lead a high-performing ML team and roadmap.
• Lead the development of visuomotor policies and experiments.
• Define robust real-robot and sim evaluation protocols.
• Establish regression testing to ensure measurable improvements.
• Ship production-quality models and collaborate with cross-functional teams.
• Foster partnerships with academic and industry collaborators.

Skills

Team management

Python PyTorch

ML research

Data management

Production deployment

Experimentation culture

Education

PhD or MSc or equivalent

Job description

Team Lead Machine Learning, Physical AI (f/m/d)

We're hiring a Team Lead Physical AI to lead a team that turns human demonstrations into reliable manipulation skills on our humanoid platform. You will own the path from teleoperated demonstration to deployed policy: how we collect data, what we train on it, and how we prove it works on real robots in real customer environments.

This is a leadership role with a hands-on core. You will hire, mentor, and manage the team and own its roadmap, while staying technically involved across our imitation learning stack.

Your Mission

• Build and lead a high-performing team — recruit, mentor, and grow a team of ML engineers and researchers. Set a culture of rapid experimentation with rigorous evaluation, and keep the team's roadmap honest about what is research and what is delivery.
• Lead the technical development of visuomotor policies — build the technical roadmap, prioritize directions for improvement, review experiments and code, unblock the team, and take on the hard problems yourself.
• Set the bar for evaluation — build real-robot and simulation evaluation protocols with enough statistical rigor to support go/no-go decisions.
• Establish regression testing so improvements are measurable and failures are diagnosable.
• Ship models into production — work closely with the Product, MLOps, Controls, and Hardware teams to deploy policies on our robots in challenging customer environments, and to close the loop on failures observed in the field.
• Leverage and build partnerships — co-engineer with strategic partners to accelerate development and stay at the frontier. Help build new strategic partnerships and academic collaborations.

Your Skillset

Must-have

• Deep, hands‑on expertise with ML research and development (PhD, MSc, or equivalent industry experience)
• 2+ years experience managing or technically leading a team (hiring, roadmapping, mentoring), with the appetite to keep doing both people and technical work
• Professional experience training and deploying ML models, with strong Python and deep learning framework skills (PyTorch)
• Practical experience managing and scaling datasets
• Track record of translating research into working systems (papers + shipped product/demo)
• Comfort operating in a fast‑paced startup‑like environment inside a larger organization

Strong advantage

• Experience with imitation learning and/or reinforcement learning for robotic manipulation
• Experience with robotic manipulation on humanoid, bimanual, or mobile manipulation platforms
• Experience with teleoperation systems and the tooling around them
• Familiarity with diffusion and flow‑matching policies, action chunking, and modern VLA architectures
• Distributed training at scale and mature experiment tracking practice
• Publications or visible contributions in imitation learning, embodied AI, or robot learning

What You’ll Get

• Flexible working hours and a hybrid model for real work‑life balance
• CHF 500 mobility credit for sustainable commuting
• Bonus system & strong pension contributions
• Tailored training & development opportunities
• Relocation support for a smooth start
• Discounts on health, mobility & entertainment
• Team events and a flat hierarchy where your voice counts
• A warm, international culture built on respect and collaboration