Senior Deep Learning Researcher – Physical AI - Qualcomm

Company:

Qualcomm Technologies Netherlands B.V.Job Area:

Engineering Group, Engineering Group  Machine Learning Researcher General

Summary:

At Qualcomm AI Research, we advance AI to make perception, reasoning, and action ubiquitous across devices. Our mission is to drive fundamental breakthroughs in AI and translate them into real-world impact at scale.

A key pillar of our research agenda is Physical AI: intelligent systems that learn to perceive, reason, and act through embodied interaction with the physical world. We pursue research that tightly integrates learning, robotics, and real-world experimentation, with a strong emphasis on scientific rigor, business impact, and thought leadership.

Job Summary:

We are seeking a Senior Deep Learning Researcher in Physical AI / Embodied AI to join our Amsterdam-based research team. The ideal candidate is a scientifically strong deep learning researcher with extensive experience in embodied AI and real robot experiments, and deep expertise in at least one core area relevant to Physical AI.You will be joining a well-established and innovative Physical AI research team that brings together researchers with strong academic backgrounds and extensive experience in embodied AI and robotics.

You will have access to a diverse fleet of real robotic platforms, including humanoid robots and high-degree-of-freedom robot arms, enabling rigorous experimental validation beyond simulation. The team regularly conducts hands-on research in dexterous manipulation, loco-manipulation, and multimodal sensing, including vision, tactile, and force feedback. In addition, the team collaborates closely with robot OEM partners around the world, providing opportunities to influence real robotic systems and align scientific research with practical deployment considerations.

This role is research-driven, with the objective to develop impactful breakthroughs in Physical AI. We offer opportunity to publish at top-tier venues, while maintaining a clear connection to real robotic systems—particularly humanoid robots and dexterous manipulation.

We are particularly interested in candidates with proven machine learning research background and deep expertise in one or more of the following areas, applied to embodied agents and real robotic systems:

Reinforcement learning, self-supervised learning, self-play for dexterous manipulation

Dexterous manipulation, including tactile and force-based control

Learning from multimodal sensory inputs (vision, proprioception, force, tactile sensing)
Loco-manipulation for humanoid robotics

Vision-Language-Action (VLA) models for embodied intelligence

Key Responsibilities:

Conduct original research in Physical AI and Embodied Intelligence that creates business and scientific impact.

Design and evaluate learning-based methods in simulation and on real robots, with emphasis on humanoid platforms and manipulation.

Develop models that integrate perception, language, and action under real-world physical constraints.

Publish research in top-tier conferences and journals (e.g., NeurIPS, ICML, ICLR, CoRL, RSS, ICRA).Collaborate with other researchers and engineers to ensure long-term impact and relevance.

Contribute to Qualcomm AI Research’s research strategy and scientific visibility in Physical AI.Requirements:

PhD in Machine Learning, Deep Learning, Robotics, Computer Vision, or a closely related field, or equivalent practical experience.

Deep expertise in at least one of the above-mentioned areas.

Excellent programming skills in Python and experience with modern deep learning frameworks (PyTorch, JAX).Ability to design clean experimental pipelines and write maintainable research code.

Strong track record of scientific publications in top-tier machine learning and/or robotics venues.

Preferred Qualifications:

Proven experience with embodied AI and real robot experiments, beyond purely simulated work.

Experience bridging simulation and real-world robotics (sim-to-real, system identification, data collection).Hands-on experience with humanoid or high-DoF manipulation platforms.

Prior experience in industrial research environments with strong scientific output.

The role is based out of…