Machine Learning Research Engineer

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Researcher

General Summary:

About the Team: Qualcomm’s Applied ML R&D for HW Design team develops ML/AI or algorithmic based design tools which improve the overall chip design process and quality through NRE and/or AuC reduction or performance improvement. We are an interdisciplinary team with backgrounds in Computer Science, ML/AI, Electrical Engineering, Computer Engineering, Physics, Neuroscience, Economics, and VLSI Design, united by our passion to solve challenging problems. We work cross-functionally over the entire chip design process and are motivated by the chance to pursue technical innovations which provide real value to the Qualcomm product line. The ultimate goal for our research is to be productized and packaged into a design tool used in the Qualcomm chip design execution process.

About the Role: We are seeking a highly skilled Applied ML Research Engineer to research, develop, and deploy solutions to accelerate the chip design process and who is passionate about building, delivering, and seeing their work realized in end-to-end products used to design Qualcomm chips.

In this role, you will:

• Work in a team of ML, CAD, and HW engineers to deliver technologies which compose a multi-component system
• Explore and define technical solutions to meet system requirements.
• Work closely with your co-developers to ensure seamless integration and alignment across all components in the overall system.
• Collaborate with a cross-functional team of hardware engineers, CAD engineers, and IT engineers to integrate AI-driven solutions into the chip design pipeline
• Conduct Exploratory Data Analysis (EDA) to uncover insights and inform model development.
• Develop advanced models and algorithms to solve complex problems.
• Perform feasibility studies to assess the viability of proposed solutions.
• Implement research pipelines to streamline the development process.
• Write detailed specifications describing the implemented approach, assumptions, and limitations.
• Evaluate solutions on provided test cases against specified metrics and benchmarks.
• Deliver prototype solutions, including both the approach and software.
• Explore and craft datasets, metrics, experiments, and validation scripts to establish standard methodologies for research
• Stay up-to-date with the latest developments in the domain of ML/AI and ML/AI for Chip Design
• Write documentation and training materials to help teammates and customers understand and utilize research findings

Required Skills and Qualifications:

• Master's or Ph.D. degree in Computer Science, computer engineering, Electrical Engineering, Statistics, or a related field.
• Strong background in machine learning, deep learning, and statistical modeling.
• Proficiency in programming languages such as Python.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Proven ability to conduct feasibility studies and explore technical solutions.
• Ability to test and evaluate solutions against metrics and benchmarks.
• Excellent communication skills to collaborate effectively with cross-functional teams.
• Familiarity with software development best practices and version control systems like Git.

Preferred Qualifications:

• Hands-on experience with Generative AI models (e.g., LLMs, diffusion models).
• Experience with big data technologies such as Hadoop, Spark, and cloud platforms like AWS, Azure, or Google Cloud.
• Publications in reputable journals or conferences in the field of machine learning.

Minimum Qualifications:

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

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

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.

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.

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.

 

Pay range and Other Compensation & Benefits:

$179,000.00 - $268,600.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm.  We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus).  In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.

If you would like more information about this role, please contact Qualcomm Careers.