Q

Qualcomm

Designs mobile chips and licenses wireless patents

Senior Engineer - AI Model Enablement & Software Tools, Machine Learning Engineering

Full-TimeUpdated on 10/23/2026
$140.8k - $211.2k+ Annual discretionary bonus + Annual RSU grants
Junior, Mid, Senior
Bachelor's, Master's, PhD
San Diego, CA, USA
In Person
AI & Machine LearningApplied Machine Learning
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • A bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field is required.
  • Engineer-level candidates must have project or internship experience, or at least 1 year of software development experience.
  • Senior Engineer candidates must have at least 2 years of experience in software design, development, and delivery.
  • Good programming skills in Python and/or C/C++ are required.
  • A strong understanding of software engineering fundamentals, including data structures, algorithms, object-oriented design, debugging, testing, and source control, is required.
  • A foundational understanding of AI/ML concepts, including neural networks, deep learning, model inference, and common model execution workflows, is required.
  • Practical experience using agentic coding tools such as Claude Code, OpenAI Codex, or equivalent for code exploration, implementation, testing, and debugging, and the ability to review and validate generated code, are required.
  • The ability to read and understand unfamiliar software and model implementations is required.
  • Strong analytical and debugging skills, including structured root-cause analysis, are required.
  • The ability to collaborate effectively within a team and communicate technical concepts clearly is required.
  • The ability and willingness to learn model architectures, graph processing, quantization, compiler, runtime, and hardware-aware optimization concepts are required.
  • A bachelor's degree in Computer Science, Engineering, or Information Systems, or a related field, plus 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience; or a master's degree in those fields plus 1+ year of related work experience; or a PhD in those fields, is listed in the additional minimum qualifications.
Responsibilities
  • Contribute to bringing up and enabling new language, vision, vision-language, and multimodal models on Snapdragon platforms.
  • Study model implementations and computational graphs to understand model inputs, outputs, operators, tensor shapes, data flow, and execution behavior.
  • Work with AI Research and backend teams to identify unsupported operators, graph patterns, precision constraints, and performance limitations.
  • Implement model re-authoring, operator decomposition, graph transformations, layout changes, and backend-specific adaptations.
  • Develop reusable model support for integration into Qualcomm's model-enablement frameworks rather than creating isolated model-specific solutions.
  • Implement and maintain pipeline stages, model mappings, quantization recipes, configuration models, artifact handling, and validation utilities.
  • Convert, optimize, and export models from PyTorch and ONNX for compilation and execution on Qualcomm AI accelerators.
  • Apply and validate quantization and calibration flows, including weight and activation quantization, mixed precision, post-training quantization, and accuracy-recovery techniques.
  • Measure and improve model accuracy, latency, throughput, memory consumption, model size, and power efficiency.
  • Work with generative AI inference concepts such as transformer attention, KV cache, prefill and decode execution, LoRA, mixture of experts, and speculative decoding.
  • Support vision and multimodal processing flows, including image processors, vision encoders, language backbones, and cross-component artifact integration.
  • Debug issues across model code, computational graphs, quantization, compiler, runtime, operating system, and hardware layers.
  • Develop unit, integration, accuracy, performance, and on-device validation tests.
  • Write high-quality, maintainable, and well-documented Python and C/C++ code.
  • Participate in technical discussions, design reviews, code reviews, debugging sessions, and testing cycles.
  • Collaborate with globally distributed engineering, research, hardware, quality assurance, product, and customer-facing teams.
  • Senior Engineers independently own larger features, contribute to design decisions, mentor junior engineers, and drive assigned model-enablement work through completion.
Desired Qualifications
  • A master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field is preferred.
  • Coursework, internship, project, or professional experience involving AI/ML inference, model optimization, or embedded AI software is preferred.
  • Familiarity with PyTorch, ONNX, Hugging Face Transformers, or related AI/ML frameworks is preferred.
  • Familiarity with graph-based model representations and tooling such as ONNX, TorchScript, MLIR, ONNX Runtime, ExecuTorch, or TFLite/LiteRT is preferred.
  • A basic understanding of model quantization and calibration, including post-training quantization, quantization-aware training, weight and activation quantization, and mixed precision, is preferred.
  • Experience or coursework involving transformer-based models, large language models, vision models, or multimodal models is preferred.
  • Understanding of common transformer components such as attention, normalization, feed-forward layers, positional encoding, and KV cache is preferred.
  • Experience with Linux-based software development is preferred.
  • Experience developing or optimizing embedded, mobile, edge, or system-level software is preferred.
  • Exposure to Android or a real-time operating system environment such as QNX is preferred.
  • Familiarity with CMake-based builds, Git-based source control, code reviews, and agile software development practices is preferred.
  • Experience writing unit tests, integration tests, and debugging software across multiple abstraction layers is preferred.
  • Exposure to model performance analysis, profiling, memory optimization, or hardware accelerator programming is preferred.
  • User-level or development exposure to commercial AI software stacks and model-enablement frameworks, including model conversion, optimization, compilation, deployment, and runtime tools, is preferred.
  • Exposure to Snapdragon SoCs, NPUs, HTPs, or other AI accelerator architectures is preferred.

About the company

Qualcomm designs the Snapdragon processors and modems inside many Android phones, and it licenses its wireless patents to device makers around the world. It helped commercialize CDMA, the cellular technology behind 3G networks, and its patents cover core parts of the 4G and 5G standards that phones use to connect. The company does not run its own chip factories; contract foundries make its chips, which it sells to makers of phones, PCs, cars, and connected devices. Device makers also pay Qualcomm royalties for using its patented technology, which forms a second business alongside chip sales. Qualcomm was founded in 1985 and is based in San Diego, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

San Diego, California

Founded

1985

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Simplify Jobs

Simplify's Take

What believers are saying

  • Cars are a second engine: automotive chip revenue rose 61% to $1.59 billion in the June 2026 quarter.
  • Pays for learning: Qualcomm funds tuition assistance and apprenticeships and sells staff discounted shares through a stock purchase plan.
  • Profits support stability: Qualcomm earned $2.21 non-GAAP per share in the June 2026 quarter despite a 4% sales dip.

What critics are saying

  • Apple is walking away: Qualcomm expects Apple revenue to fall about 50% from the September to December 2026 quarter.
  • Data-center deals start thin: in July 2026, management said custom chips will cut chip gross margin 1.5 to 2 points.
  • Cuts keep trickling: Qualcomm filed WARN notices in April 2026 covering 144 layoffs, including 68 in San Diego.

What makes Qualcomm unique

  • Phones are only part of it: handsets were $5.09 billion of $8.50 billion chip revenue in fiscal Q3 2026.
  • Cloud giants buy its custom chips: two hyperscaler design wins start producing revenue in the December 2026 quarter.
  • It owns an AI software layer: Qualcomm completed its Modular acquisition in July 2026 for open generative AI software.

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Benefits

  • Premium-free health coverage
  • Onsite health & fitness centers
  • Retirement programs
  • Disability & life insurance programs
  • Tuition reimbursement
  • Product discounts
  • Flexible time off
  • Parental leave

Growth & Insights and Company News

6 month growth

3%

1 year growth

1%

2 year growth

0%
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