Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
As an Engineer / Senior Engineer in the Qualcomm AI Stack SDK Software team, you will contribute to bringing modern AI models to Snapdragon platforms using Qualcomm's AI software stack and model-enablement frameworks.
You will work with senior engineers to analyze, adapt, optimize, quantize, compile, and validate AI models, including Large Language Models, vision models, Vision-Language Models, and multimodal models. You will collaborate with AI Research and AI accelerator hardware and software teams to understand model architectures, identify operator- and graph-level backend gaps, and integrate reusable solutions into Qualcomm's model-enablement frameworks and SDK.
This role combines AI/ML software development with graph processing, model optimization, systems software, and on-device execution. You will gain hands-on experience with model loading, graph adaptation, quantization, calibration, compilation, runtime integration, performance analysis, and debugging across software and hardware layers.
The role emphasizes strong programming fundamentals, hands-on implementation, problem-solving, and collaboration. Engineers will work under the guidance of technical leads, while Senior Engineers will take greater ownership of feature design, implementation, debugging, and delivery.
Responsibilities
• Contribute to the bring-up and enablement of 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 that can be integrated 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, PTQ, 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, MoE, 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, QA, product, and customer-facing teams.
• Senior Engineers will independently own larger features, contribute to design decisions, mentor junior engineers, and drive assigned model-enablement work through completion.
Minimum Qualifications (Must Have)
• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Engineer: Project or internship experience for entry-level candidates, or 1+ years of experience in software development.
OR
• Senior Engineer: 2+ years of experience in software design, development, and delivery.
• Good programming skills in Python and/or C/C++.
• Strong understanding of software engineering fundamentals, including data structures, algorithms, object-oriented design, debugging, testing, and source control.
• Foundational understanding of AI/ML concepts, including neural networks, deep learning, model inference, and common model execution workflows.
• Practical experience using agentic coding tools such as Claude Code, OpenAI Codex, or equivalent tools for code exploration, implementation, testing, and debugging, with the ability to review and validate generated code.
• Ability to read and understand unfamiliar software and model implementations.
• Strong analytical and debugging skills, with the ability to perform structured root-cause analysis.
• Ability to collaborate effectively within a team and communicate technical concepts clearly.
• Ability and willingness to learn model architectures, graph processing, quantization, compiler, runtime, and hardware-aware optimization concepts.
Preferred Qualifications
• Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Coursework, internship, project, or professional experience involving AI/ML inference, model optimization, or embedded AI software.
• Familiarity with PyTorch, ONNX, Hugging Face Transformers, or related AI/ML frameworks.
• Familiarity with graph-based model representations and tooling such as ONNX, TorchScript, MLIR, ONNX Runtime, ExecuTorch, or TFLite/LiteRT.
• Basic understanding of model quantization and calibration, including PTQ, QAT, weight and activation quantization, and mixed precision.
• Experience or coursework involving transformer-based models, LLMs, vision models, or multimodal models.
• Understanding of common transformer components such as attention, normalization, feed-forward layers, positional encoding, and KV cache.
• Experience with Linux-based software development.
• Experience developing or optimizing embedded, mobile, edge, or system-level software.
• Exposure to Android or an RTOS environment such as QNX.
• Familiarity with CMake-based builds, Git-based source control, code reviews, and agile software development practices.
• Experience writing unit tests, integration tests, and debugging software across multiple abstraction layers.
• Exposure to model performance analysis, profiling, memory optimization, or hardware accelerator programming.
• User-level or development exposure to commercial AI software stacks and model-enablement frameworks, including model conversion, optimization, compilation, deployment, and runtime tools.
Exposure to Snapdragon SoCs, NPUs, HTPs, or other AI accelerator architectures.
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.
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.
