Shire Jobs

Company:

Qualcomm Technologies Netherlands B.V.

Job Area:

Engineering Group, Engineering Group > Machine Learning Researcher

General Summary:

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.

As Senior Machine Learning Researcher at Qualcomm, you develop and quickly iterate on innovative research ideas, and prototype and implement them in collaboration with other researchers and engineers. You stay up to date with the latest research in the field and publish papers at scientific conferences. You create impact and engage with other teams to see your ideas deployed on millions of devices, such as mobile phones, AR/VR headsets, or autonomous vehicles.

We are looking for a Senior Machine Learning Researcher to join our team dedicated to advancing the state-of-the-art in efficiency of foundation models. The team focuses on developing innovative techniques in Model Quantization, Model Compression, and Conditional Computation methods such as sparse Mixture of Experts (MoEs). Our work spans across various Generative AI tasks, including Large Language Models (LLMs), Vision-Language Models (VLM), and Multi-modal Language Models (MLM).

You have a background in one or more of the following: optimization, model quantization, model compression, dynamic sparsity and MoEs, or classical search algorithms. You have experience with LLMs, Vision-Language Models, Multi-modal Models, or related AI models, demonstrated through publications in top-tier conferences.

Working at Qualcomm means being part of a global company (headquartered in San Diego) that fosters a diverse workforce and puts emphasis on the learning opportunities and professional development of its employees. You will work closely with researchers that have published at major conferences, work on campus co-located with the University of Amsterdam, and live in a scenic, vibrant city with a healthy work/life balance and a diversity of cultural activities.

In addition, you can join plenty of mentorship, learning, peer, and affinity group opportunities within the company. In this way you can easily develop personal and professional skills in your areas of interest. You’re empowered to start your own initiatives and, in doing so, collaborate with colleagues in offices across teams and countries.

Minimum qualifications:

• PhD or Master’s degree in Machine Learning, Computer Vision, Physics, Mathematics, Electrical engineering or similar field, or equivalent practical experience

• Experience in machine learning, deep learning, and/or reinforcement learning

• Ability to formulate research problems and design, experiment and implement solutions

• Programming experience in Python and hands-on experience with deep learning toolkits such as PyTorch, TensorFlow, Jax

Preferred qualifications:

• Track record of publishing at major conferences in machine learning (NeurIPS, ICML, ICLR, CVPR, etc.)

• Hands-on experience with foundation models (LLMs, LVMs) is a strong plus

• Experience in writing clean and maintainable code for research-internal use (no product development)

• Experience working in an academic or industry research lab

Minimum Qualifications:

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.

• 6+ months of academic and/or work experience developing and/or optimizing machine learning models, systems, platforms, or methods.

*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail myhr.support@qualcomm.com or call Qualcomm's toll-free number found here (https://qualcomm.service-now.com/hrpublic?id=hr_public_article_view&sysparm_article=KB0039028) . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) .

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification