Sr Software Engineer, AI Tools – AI/ML Compiler

Qualcomm; San Diego (CA); On-site; USD 140,800 - 211,200; Full time

Benefits offered by this job

Competitive annual discretionary bonus

Annual RSU grants

Highly competitive benefits package

Job summary

Qualcomm in San Diego is looking for a Machine Learning Engineer to implement graph optimization passes and develop AI solutions. The role emphasizes collaboration with engineering teams and requires experience in ML systems and Python programming.

The position offers a competitive salary range of $140,800.00 – $211,200.00, along with bonuses and a robust benefits package designed to support employee well-being and success.

Qualifications

• 4+ years in Software Engineering, ML Engineering, or related experience.
• Experience in ML systems, model optimization, or inference engineering.
• Proficient in Python in large, typed codebases.

Responsibilities

• Implement new ONNX graph optimization passes.
• Write match logic that identifies specific subgraph shapes.
• Validate transformations end-to-end using ONNX Runtime.

Skills

ML systems

Model optimization

Python programming

Graph algorithms

Communication skills

Education

Bachelor's degree in Computer Science, Engineering, or related field

Master's degree in Computer Science, Engineering, or related field

PhD in Computer Science, Engineering, or related field

Tools

ONNX Runtime

PyTorch

Job description

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.

Locations: San Diego, CA and Raleigh, NC. Full‑time, onsite location required.

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

• Bachelor's degree in Computer Science, Engineering, or related field and 4+ years of Software Engineering, ML Engineering, or related experience.
• OR Master's degree in Computer Science, Engineering, or related field and 3+ years of relevant experience.
• OR PhD in Computer Science, Engineering, or related field and 2+ years of relevant experience.
• 2+ years in ML systems, model optimization, or inference engineering. Proficient in Python in large, typed codebases.
• Strong written and verbal communication. Comfortable operating across compiler, 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).

Equal Opportunity Employer & EEO Statement

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 disability‑[e-mail]. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able to participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities.

Pay Range and Benefits

Pay range: $140,800.00 – $211,200.00. In addition to base salary, the compensation package includes a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales‑incentive plans are not eligible for our annual bonus). Qualcomm also offers a highly competitive benefits package designed to support your success at work, at home, and at play.