Machine Learning R&D

Qualcomm
San Diego, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 211K

Job location

Remote
San Diego, United States of America

Tech stack

Java
Artificial Intelligence
Systems Engineering
C++
Information Systems
Computer Engineering
High-Level Architecture
Python
Machine Learning
Product Management
TensorFlow
Software Engineering
PyTorch
Large Language Models
Generative AI
Scikit Learn
Information Technology
Machine Learning Operations
Virtual Agents

Job description

About the Role: We are seeking a candidate who can provide technical execution and leadership in Machine Learning/AI R&D including Generative AI and its applications in chip design. The candidate should be passionate about seeing their research realized in end-to-end products used to design Qualcomm chips. The candidate will serve as a technical contributor and lead to an interdisciplinary team of ML researchers, ML SW engineers, and HW designers. The candidate will provide leadership by coaching others to complete tasks as well as contribute to the technical delivery of the overall project. The ideal candidate should have experience in leading and developing Generative AI projects both from R&D and product development aspects. This should include technical hands-on experience with embedding models, LLM and agentic AI post-training optimization. In addition, the candidate should have experience in complex ML SW project development processes and pipelines., * Executes on the design and delivery of Agentic AI for HW design.

  • Identifies and enables the pursuit of measurably impactful technical ideas and research directions for GenAI applications in HW design.
  • Collaborates with and coaches others to complete tasks and achieve goals.
  • Aligns individual growth with project and department goals.
  • Manages ambiguity across situations while ensuring deadlines are met.
  • Engages with cross-functional teams to identify and deliver solutions for technical gaps and opportunities.
  • Contributes to 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.

Requirements

  • PhD in Computer Science, Electrical Engineering, or a related field.
  • At least 2 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, Langchain, Agno).
  • 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, * Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience., Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field.

Benefits & conditions

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 : $140,800.00 - $211,200.00

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 .

About the company

Qualcomm Technologies, Inc., 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.

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