Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation AI experiences and drive agentic transformation, creating a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will develop and implement cutting-edge tools and solutions to enable state-of-the-art AI solutions across various technology verticals.

All Qualcomm employees are expected to actively support diversity on their teams, and in the Company.

This role is open to both San Diego, CA and Raleigh, NC and will be onsite full-time.

Minimum Qualifications:

• 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.

OR
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.

What You'll Do

Graph Optimization Passes

• Implement new ONNX graph optimization passes under technical guidance from senior engineers. Work spans pattern matching, dead code elimination, op fusion, reshape/transpose simplification, and layout transforms.
• Extend existing passes to handle new operator patterns, edge cases, and opset variations.
• Write rewrites that follow established compiler engineering practices for clarity, modularity, and testability.

Pattern Matching & Graph Rewriting

• Write match logic that identifies specific subgraph shapes. This means inspecting op types, attributes, tensor shapes, and producer chains.
• Implement rewrites that transform matched patterns. The rewrites need to preserve graph correctness and any metadata that downstream stages depend on, such as quantization information.
• Reuse existing graph traversal and rewriting utilities rather than reimplementing common operations.

Testing & Validation

• Write unit tests that exercise new passes against synthetic and real ONNX models. Use IR-level diff checks to confirm transformations produce the expected graph.
• Validate transformations end-to-end using ONNX Runtime. Compare numerical outputs of the pre- and post-optimized models against tolerance thresholds.
• Maintain and extend test fixtures as optimization coverage grows.

Cross-Functional Collaboration

• Work closely with engineers on the optimizer team to ramp up on the codebase. Learn how compiler-style optimizations are designed and reviewed in production.
• Coordinate with quantization and model preparation engineers. Understand how optimizer output flows into the rest of the deployment pipeline.

Minimum Qualifications

• Experience in ML systems, model optimization, or inference engineering. Proficient in Python in large, typed codebases.
• Strong written and verbal communication. Comfortable operating across AI compiler, AI research, and partner-facing teams.

Preferred Qualifications

• Working knowledge of graph concepts: intermediate representations, graph traversal, pass-based optimization, pattern matching, and fixed-point iteration.
• Familiarity with the ONNX format, operator semantics, and opset versioning. A strong willingness to ramp up quickly is fine if you don't have all of this yet.
• Comfortable with graph algorithms — DFS/BFS, topological sort, basic dataflow analysis.
• Exposure to ONNX Runtime, PyTorch, or another ML framework for model inspection and validation.
• A working sense of model quantization is a plus.
• Strong written and verbal communication. Comfortable asking questions, seeking feedback, and learning quickly from code review.
• Experience using agentic coding tools such as GitHub Copilot, Cursor, Claude Code, Codeium, or similar AI-assisted development tools to improve coding productivity and problem-solving.

Level of Responsibility

• Works on well-scoped optimization tasks under technical guidance from team members.
• Receives mentorship and grows toward independent ownership of optimization passes and the surrounding test infrastructure.
• Decisions have focused impact. They affect individual passes, test coverage, and pipeline correctness in the immediate area.
• Communicates primarily within the optimizer team and adjacent teams (quantization, model preparation).

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 :

$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 .

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