Senior Deep Learning Researcher - Generative Vision

Company

Qualcomm Technologies Netherlands B.V.

Engineering Group, Engineering Group >
Machine Learning Researcher

At Qualcomm AI Research, we are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous across devices. Our mission is to make breakthroughs in fundamental AI research and scale them across industries. By bringing together some of the best minds in the field, we're pushing the boundaries of what's possible and shaping the future of AI.

We are seeking a talented Senior Deep Learning Researcher to join our team. The ideal candidate will have a background in deep learning with proven academic and/or industrial research experience, and a passion for pushing the boundaries of AI technology. You will have the opportunity to work on cutting-edge projects as part of our Amsterdam-based research teams.

We are currently looking for candidates to join our teams in the following research area:

The team’s mission is to make large vision and multimodal generative models accessible to everyone by optimizing them to run on small devices, e.g., phones, cars, and XR headsets. This involves research on efficient generative models (i.e., diffusion and autoregressive), efficient transformers and alternatives (e.g., state space models, RNNs, linear attention), distillation and pruning of models to generate image, video and 3D content.

• You conduct research and develop and quickly iterate on innovative deep learning-based models and algorithms. You design, experiment, and implement novel solutions that advance the state-of-the-art, in close collaboration with other researchers and engineers.
• Through your research, you create scientific as well as business impact, helping us develop impactful breakthroughs in AI Research. You engage with other teams to see your ideas deployed on millions of devices, such as mobile phones, AR/VR headsets, or autonomous vehicles.
• You stay up to date with the latest advancements in AI and machine learning. You publish novel research findings in top-tier conferences and journals and engage with the academic community.

• You have a PhD in Machine Learning, Computer Vision, Physics, Mathematics, Electrical engineering or similar field, or equivalent practical experience.
• You have proven experience in deep learning and machine learning research, including hands-on experience developing and optimizing models, and are comfortable with all aspects of the research cycle.
• You have programming experience in Python and hands-on experience with standard deep learning toolkits such as PyTorch, Jax. You write clean and maintainable code for research and advanced prototyping and follow best practices.
• You have strong problem-solving abilities and a collaborative mindset.

• Extensive experience in deep learning research and impactful publications in top-tier conferences and journals (NeurIPS, ICML, ICLR, CVPR, etc.).
• Experience working with a variety of stakeholders and ability to communicate complex outcomes to a wide range of audiences.
• Prior experience working in an industrial research setting and/or technology leadership experience are a strong plus.
• Prior experience with hardware accelerators for deep learning.

The role is based out of our Amsterdam office, and we are not seeking remote-based candidates.

At Qualcomm AI Research, you will be part of a team with a wide range of backgrounds that values innovation and creativity. Our commitment to professional growth and development ensures that all team members can thrive and contribute their unique perspectives to making research and business impact.

You will be part of a global company (headquartered in San Diego) and work closely with exceptional researchers and engineers that publish at major conferences.

Additionally, you will be based in Amsterdam, a scenic, vibrant city known for its picturesque canals, rich history, and dynamic cultural scene, making it a wonderful place to live and work.

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or…