Machine Learning R&D

About the Role: We are seeking a candidate who can provide technical leadership in Machine Learning/AI R&D, including Generative AI and its applications in chip design. The candidate will serve as a senior technical lead to an interdisciplinary team of ML researchers, ML software engineers, and HW designers, coaching others and contributing to the technical delivery of the overall project. The ideal candidate should have experience leading and developing Generative AI projects from R&D and product development, including hands-on experience with embedding models, LLM and agentic AI post-training optimization, and complex ML SW project development processes and pipelines., * Oversee the design and delivery of an internal benchmark suite for LLMs for hardware design for GenAI applications.

• Oversee the design and delivery of Agentic AI for HW design.
• Identify and enable the pursuit of measurably impactful technical ideas and research directions for GenAI applications in HW design.
• Coaches others to complete tasks and achieve goals.
• Aligns individual growth with department goals.
• Manages the project team’s capabilities and ambiguity across situations while ensuring deadlines are met.
• Engages with cross-functional teams to identify technical gaps and opportunities.
• Defines and continually updates technical project goals and roadmaps.
• Guides the team’s innovation engine from idea to execution.
• Develops effective working relationships with cross-functional and/or external stakeholders.
• Communicates effectively with partner teams, providing timely updates on project status and expectations.
• Stays current on AI, systems, and hardware-software advances relevant to the field of AI for chip design.
• Exemplifies and encourages respect, dignity, and fairness; contributes to a positive culture.

• PhD in Computer Science, Electrical Engineering, or a related field.
• At least 5 years of industry experience in Machine Learning/GenAI and MLOps.
• Industry experience in ML/AI product development and deployment.
• Deep knowledge of foundational model architectures and industry experience in foundation model development.
• Proficiency in programming languages such as Python, Java, or C++.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Hands-on industry expertise in Agentic AI tools, frameworks, and best practices (e.g., Codex, Claude Code, OpenCode, Langchain).
• Excellent problem-solving skills and attention to detail.
• Strong communication skills and ability to work collaboratively in a team environment.
• Ability to manage multiple highly complex projects while meeting quality expectations and adhering to the company’s standards of ethical behavior.
• Ability to encourage continuous improvement and alternative viewpoints to challenge ingrained practices.
• Ability to set clear expectations.
• Ability to provide constructive feedback to encourage skills growth., * Master’s degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 6+ 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 4+ 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.

Pay range: $192,700.00 - $289,100.00. This range reflects the broad, minimum to maximum, pay scale for this job code at the location for which it has been posted. In addition to base salary, the role offers a competitive annual discretionary bonus program and the opportunity for annual RSU grants. Qualified employees may receive other benefits as part of Qualcomm’s overall compensation package. #J-18808-Ljbffr

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 across 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 that provide real value to the Qualcomm product line. The ultimate goal is to productize and package our research into a design tool used in Qualcomm’s chip design execution process.