Qualcomm

Lead the architecture, development, integration, and deployment of AI software for automotive platforms. Serve as a technical interface for automotive customers and internal teams, translating requirements into roadmaps and production-ready solutions across computer vision, driver monitoring, voice AI, and generative AI. Guide cross-functional engineering efforts and mentor engineers. Responsibilities Lead technical engagement with automotive business units, OEMs, Tier-1 suppliers, and strategic customers. Represent the organization in customer discussions, architecture reviews, technical deep dives, and issue resolution. Coordinate design, development, integration, and delivery of AI software features for automotive platforms. Translate customer and market requirements into technical specifications, architecture proposals, roadmaps, and execution plans. Improve AI software capabilities across model preparation, optimization, runtime, inference, tooling, and developer workflows. Guide cross-functional teams, make architecture decisions, mentor engineers, and ensure automotive performance, reliability, security, and safety requirements are met. Required Skills AI software architecture Machine learning Model preparation and optimization AI inference and runtime Computer vision Perception systems Driver monitoring systems Voice assistants Large language models Automotive software integration

Lead software architecture and enablement for PCIe, CXL, and interrupt controller subsystems on next-generation ARM server platforms. Work across silicon, firmware, Linux, virtualization, validation, and customer teams to deliver scalable, standards-compliant datacenter solutions. Responsibilities Define architecture, requirements, and enablement strategy for PCIe, CXL, and interrupt controller subsystems. Drive software enablement across UEFI/EDK2, Arm Trusted Firmware, Open BMC, Linux, hypervisors, and datacenter operating systems. Collaborate with So C, CPU, hardware, firmware, kernel, validation, and product teams on production-ready solutions. Define platform requirements for ARM, PCI-SIG, CXL, ACPI, UEFI, and datacenter standards compliance. Lead architecture reviews and integrate software requirements into silicon, firmware, and platform designs. Develop system-level strategies for performance, RAS, debug, telemetry, error handling, fault isolation, and recovery. Required Skills ARM server architecture PCIe CXLARM GICLinux kernel internals C/C++UEFI/EDK2 Arm Trusted Firmware KVM and hypervisors Platform firmware

Build and maintain the compilation infrastructure for Qualcomm AI Hub, transforming PyTorch and ONNX models into deployable artifacts for Qualcomm devices. Develop graph optimization and backend execution paths, validate model performance, automate model onboarding, and create developer documentation. Responsibilities Design, develop, and maintain model compilation pipelines from Py Torch and ONNX ingestion through deployable artifacts. Build ONNX graph transformation, operator validation, and opset compatibility functionality. Maintain Py Torch compilation paths, including dynamic shapes, custom operators, and ATen IR decomposition. Contribute graph optimization, partitioning, validation, and lowering features to the ONNXRuntime QNN execution provider. Build tools to profile and debug compilation failures, accuracy regressions, and performance issues. Automate model compilation and validation, collaborate with internal teams on model onboarding, and write technical documentation. Required Skills Python C++ONNX IRPy Torch model exporttorch.export ATen IRGraph transformation Operator fusion Shape inference Compiler backend partitioning

Lead the development and optimization of embedded AI software and runtime systems for Qualcomm edge devices. Design and profile machine learning frameworks, inference tools, compilers, and agentic AI solutions, translating research into production-ready technologies while collaborating across hardware, software, and research teams. Responsibilities Lead development of embedded AI software and runtime systems for neural networks on Qualcomm hardware. Design, debug, profile, and optimize ML frameworks, runtime software, model efficiency tools, compilers, and inference. Prototype AI and agentic software solutions and translate research into production-ready technologies. Guide machine learning solution design, implementation, training, evaluation, and deployment. Improve ML software stack performance and power efficiency through hardware-software co-design. Coordinate technical direction across teams, mentor engineers, and drive strategic AI initiatives. Required Skills C/C++Python Embedded AI software development Machine learning frameworks AI runtime software Machine learning inference optimization Compiler technologies Linux Android QNX

Design security architecture for next-generation CPUs, CPU clusters and control processors. Define access-control policies, privilege models, isolation boundaries and protection mechanisms across hardware, firmware, debug resources and shared SoC systems. Collaborate with engineering teams to specify and verify secure designs, assess threats, and balance security assurance with power, performance and area requirements. Responsibilities Design CPU security features to counter potential threats. Architect access-control policies and topologies for CPU clusters and control processors. Define privilege separation, authorization checks, isolation boundaries, secure boot, and debug access policies. Specify protection requirements for security-critical registers, memories, firmware interfaces, and shared So C resources. Collaborate with hardware and software teams to implement secure design principles. Conduct security assessments and recommend architectural changes. Required Skills CPU security architecture Access-control architecture and policy design Privilege models and isolation boundaries CPU microarchitectural security threats and countermeasures CPU instruction set architectures such as ARM, x86, or RISC-VThreat modeling and security risk analysis Cryptographic algorithms and protocols Hardware design for CPU subcomponents Formal or semi-formal security verification Automated microarchitectural fuzzing

Qualcomm seeks a Staff Machine Learning Engineer to build and deploy AI/ML automation for automotive cybersecurity and functional safety engineering. You will develop LLM-powered tools, scalable ML pipelines, document review and compliance workflows, and knowledge systems across the semiconductor product lifecycle, collaborating with cross-functional engineering teams. Responsibilities Design AI/ML automation solutions for cybersecurity and functional safety workflows. Build intelligent systems for document understanding, review automation, and engineering productivity. Develop and deploy solutions using LLMs, generative AI, and agentic AI frameworks. Create knowledge automation platforms for cross-project reuse and decision support. Build scalable end-to-end automation pipelines across engineering domains. Apply AI/ML to security analysis, compliance monitoring, and process optimization. Required Skills Machine learning Artificial intelligence Large language models (LLMs) Generative AIAgentic AI frameworks Python C++Production ML pipelines Model training and inference systems Knowledge systems, semantic search, and retrieval-augmented generation (RAG)

Develop profiling, performance analysis, and debugging tools for Qualcomm Adreno GPUs. Collaborate with hardware and software teams to validate GPU performance, troubleshoot issues, optimize developer experiences, and work with partners and OEMs on tools that support next-generation graphics and compute applications. Responsibilities Design and develop GPU profiling tool features. Build performance analysis and GPU debugging tools. Collaborate with hardware and software teams on GPU performance validation and analysis. Debug issues and optimize tools for the user experience. Work with developers, partners, and OEMs to improve GPU developer tools. Support software development for next-generation Adreno GPU capabilities. Required Skills C++CGPU hardware Graphics concepts GPU profiling Performance analysis GPU debugging Graphics APIs GPU computing frameworks Real-time graphics optimization

Develop and commercialize embedded software and firmware for cloud edge and data center machine-learning applications on high-performance silicon. Work with cross-functional teams on technologies including ML acceleration, memory management, virtualization, board support packages, device drivers and real-time operating systems. Responsibilities Design and develop embedded software and firmware for cloud edge and data center machine-learning use cases. Develop board support packages and device drivers for embedded platforms. Bring up boards and implement and debug real-time operating system and embedded Linux software. Develop and test low-level C software, including unit testing and debugging on embedded platforms. Contribute to software solutions for ML acceleration, memory management, virtualization and efficient data movement. Collaborate with internal and cross-functional teams to advance and commercialize software solutions. Required Skills C programming Embedded software development Board support package development Device driver development RTOSEmbedded Linux Secure boot Trust Zone Unit testing JTAG/SWD debugging

Develop and improve infrastructure, automation, and optimization methods for next-generation CPU designs. Collaborate with physical design, CAD, methodology, and timing teams to build design tools and dashboards, analyze implementation bottlenecks, and create models for rapid timing, power, and area estimation. Responsibilities Develop infrastructure and dashboards for multiple CPU designs and domains. Collaborate with physical design, CAD, methodology, and static timing analysis teams. Analyze block-level implementation and improve optimization methods across designs. Develop prediction models for rapid timing, power, and area estimation. Use data analytics to identify and investigate design bottlenecks. Automate workflows and represent design metrics to improve productivity and scalability. Required Skills Logic synthesis Place-and-route Static timing analysis Power analysis Design signoff TCL scripting Python scripting Perl scripting Data analytics Prediction model and automation development

Qualcomm seeks a CPU Performance Analysis Engineer to optimize next generation wireless and mobile SoCs for 5G, AI, and automotive platforms. You will analyze CPU microarchitecture and system level performance, develop benchmarks and workloads, and identify bottlenecks across memory, interconnect, and power. Partner with design, architecture, and software teams to propose improvements, validate performance models, and correlate pre silicon and post silicon results. This innovative, fast paced role offers complex engineering challenges, global collaboration, and strong growth opportunities in a high impact, connectivity driven environment. Responsibilities Analyze CPU and So C performance using simulation, emulation, and silicon measurements Develop, run, and maintain performance benchmarks and workloads Identify and root cause microarchitectural and system level performance bottlenecks Collaborate with architecture and design teams to propose performance enhancements Correlate pre silicon models with post silicon measurements and refine models Generate performance reports and recommendations for future CPU and So C designs Work with software and firmware teams to optimize code for target architectures Contribute to performance tooling, automation, and data analysis pipelines Support bring up and validation of new CPU cores and So C platforms Present findings to cross functional stakeholders in a clear, data driven manner Required Skills CPU microarchitecture So C architecture Performance modeling and analysis C/C++ programming Python or similar scripting Benchmark development and profiling Linux development environment ARM or similar ISA knowledge Data analysis and visualization Simulation and emulation tools

Qualcomm seeks a Windows Power and Thermal Engineer to optimize power, performance, and thermals for next generation SoCs and AI driven devices. You will design and tune Windows power/thermal policies, develop tools and scripts, and analyze system level behavior across CPU, GPU, NPU, and RF subsystems. Collaborate with silicon, firmware, and OS teams to debug complex issues, run lab measurements, and validate features on reference and OEM hardware. Document findings, drive design recommendations, and help define best practices that improve battery life, device reliability, and user experience in global 5G and AI platforms. Responsibilities Design and optimize Windows power and thermal management strategies for Qualcomm So Cs and platforms Analyze system level power, performance, and thermal data across CPU, GPU, NPU, and RF subsystems Develop tools, scripts, and workflows to profile and tune power/thermal behavior under real world workloads Collaborate with silicon, firmware, OS, and OEM partners to debug and resolve complex system issues Perform lab measurements, bring up, and validation on reference designs and customer devices Define and refine power/thermal policies to improve battery life, performance, and device reliability Document analysis, findings, and recommendations for internal stakeholders and external partners Support enablement of AI and 5 G features with efficient power and thermal characteristics Contribute to architecture reviews and roadmap discussions for future platforms Drive best practices and guidelines for power and thermal optimization across product lines Required Skills Windows power management Thermal profiling and modeling So C architecture (CPU/GPU/NPU) Embedded firmware interaction Performance and power benchmarking Scripting in Python or Power Shell Lab measurement and instrumentation ACPI and Windows driver frameworks Data analysis and visualization System level debugging

Qualcomm seeks a Gen AI Transformation Engineer to accelerate embedded software and engineering productivity for next gen wireless and media platforms. You will design and deploy GenAI solutions across firmware, embedded OS, and toolchains to automate workflows, optimize code, and enhance developer experience. Partner with software, silicon, and DevOps teams to integrate AI copilots, code analysis, and test generation into existing pipelines. Evaluate models, build scalable inference services, measure impact on productivity, and drive best practices for secure, compliant AI adoption in a fast paced, innovation driven environment. Responsibilities Design and implement Gen AI solutions to enhance embedded software development and engineering productivity Integrate AI copilots, code generation, and static analysis tools into existing CI/CD and development workflows Collaborate with embedded, firmware, tools, and Dev Ops teams to identify and automate high value engineering use cases Build and maintain scalable Gen AI services and APIs optimized for Qualcomm hardware and software stacks Evaluate and fine tune large language models and domain specific models for code and documentation tasks Develop metrics and dashboards to measure productivity, quality, and performance impact of AI solutions Ensure AI systems follow security, privacy, and responsible AI guidelines and Qualcomm standards Create technical documentation, best practices, and internal training for AI augmented engineering workflows Required Skills Embedded software development C/C++ programming Python programming Machine learning and Gen AI (LLMs) Model integration and APIs (REST/GRPC) CI/CD pipelines and Dev Ops tooling Cloud platforms (AWS, Azure, or GCP) MLOps and model monitoring Software architecture and design Data engineering and feature pipelines

Qualcomm seeks a Staff Software Engineer for Subsystem Integration Test within our Telecommunications & Media group. You will design and develop automated test frameworks and tools to validate complex wireless subsystems across 5G, IoT, and automotive platforms. Responsibilities include creating test plans, integrating hardware and software components, analyzing logs and performance metrics, and debugging issues at system, firmware, and driver levels. You will collaborate with cross functional global teams, guide junior engineers, and ensure high quality, scalable solutions that meet aggressive performance, reliability, and interoperability goals. Responsibilities Design and implement automated subsystem integration tests for wireless platforms Develop and maintain test frameworks, tools, and scripts for 5 G and related technologies Create detailed test plans and strategies covering functionality, performance, and reliability Integrate hardware, firmware, drivers, and application software in complex test environments Analyze logs, KPIs, and performance metrics to identify defects and system bottlenecks Debug integration issues across system, firmware, and driver layers Collaborate with cross functional global teams to define requirements and resolve issues Review designs for testability and provide feedback to design and firmware teams Mentor junior engineers in test methodologies, tools, and best practices Contribute to continuous improvement of test automation, coverage, and execution efficiency Required Skills Python or similar scripting for automation Subsystem and system integration testing Test framework and tool development5 G/LTE or wireless protocol knowledge Embedded systems and firmware debugging Linux and RTOS environments Version control (Git) and CI/CD pipelines Log analysis and performance profiling Test planning and strategy C/C++ for low-level debugging

Qualcomm seeks a Staff Software Engineer for CI, build, and release pipelines supporting cutting edge wireless and 5G products. You will design, implement, and optimize scalable CI/CD systems, build orchestration, and automated release workflows for complex semiconductor and software stacks. Responsibilities include developing robust build scripts, managing artifact repositories, integrating test automation, improving reliability and performance, and enforcing quality and security gates. You'll collaborate with global engineering teams to streamline releases, troubleshoot pipeline issues, and drive best practices in DevOps, tooling, and release engineering. Responsibilities Design and maintain scalable CI/CD pipelines for wireless and 5 G-related software and tooling Develop and optimize build systems, scripts, and automation for complex semiconductor and software stacks Implement and manage artifact repositories, versioning, and release packaging workflows Integrate automated testing, quality checks, and security gates into build and release pipelines Monitor, troubleshoot, and resolve build, CI, and deployment issues across environments Collaborate with global engineering teams to streamline release processes and improve developer productivity Define and enforce best practices for CI/CD, branching strategies, and configuration management Continuously improve pipeline performance, reliability, and observability through metrics and tooling Required Skills CI/CD pipeline design and implementation Build systems (CMake, Bazel, Gradle, or similar) Source control and branching strategies (Git) Scripting languages (Python, Bash, or similar) Artifact repository management (Artifactory, Nexus, etc.) Test automation integration in CI/CDContainerization and orchestration (Docker, Kubernetes) Monitoring and observability for pipelines Linux development environments Release engineering and configuration management

Qualcomm seeks a Principal, Gen AI Transformation leader to drive large scale AI initiatives across its Telecommunications & Media portfolio. This role defines the GenAI strategy, partners with product, engineering, and business units, and converts use cases into scalable solutions spanning devices, networks, and cloud. You will lead discovery workshops, design reference architectures, and guide pilots to production, ensuring security, compliance, and performance. Collaborate with global teams to embed AI into workflows, measure business impact, and build an enterprise roadmap that accelerates innovation and competitive advantage. Responsibilities Define and drive Qualcomm's enterprise Gen AI transformation strategy across products and business units Identify, prioritize, and shape high value Gen AI use cases with telecommunications and media stakeholders Design scalable Gen AI architectures spanning device, edge, network, and cloud platforms Lead end to end delivery of Gen AI pilots and scale them to secure, compliant production solutions Collaborate with engineering, product, and operations to embed AI into tools, workflows, and services Establish governance, risk, and performance metrics for Gen AI solutions and model lifecycle Partner with data, security, and IT teams to ensure robust data pipelines and responsible AI practices Evangelize Gen AI capabilities, run workshops, and upskill internal teams on best practices Measure and communicate business impact, creating executive ready roadmaps and progress updates Stay current on AI/ML, LLM, and telecom innovations to inform Qualcomm's technology strategy Required Skills Gen AI and large language models (LLMs) Machine learning and deep learning MLOps and model lifecycle management Cloud platforms (AWS, Azure, or GCP) Data engineering and pipelines Architecture design for scalable AI systems Python or similar programming languages API integration and microservices Model evaluation, monitoring, and observability Security, compliance, and responsible AI practices

Qualcomm seeks an AI Researcher focused on on-device LLM efficiency to advance next generation wireless and mobile platforms. You will research and prototype algorithms for model compression, quantization, pruning, distillation, and on device inference optimization across smartphones, IoT, and automotive systems. Collaborating with cross functional silicon, software, and product teams, you will design experiments, benchmark models, and translate research into production ready solutions. This role offers broad impact on 5G and edge AI, strong publication opportunities, and growth in a fast paced, innovation driven environment. Responsibilities Research and develop methods for on-device LLM efficiency, including compression, quantization, pruning, and distillation Prototype and benchmark LLM inference on Qualcomm mobile, Io T, and automotive platforms Collaborate with silicon, software, and product teams to translate research into deployable solutions Design and run experiments to evaluate accuracy, latency, power, and memory trade-offs Publish and present findings internally and externally to help shape Qualcomm's AI roadmap Contribute to tooling and pipelines for efficient model deployment on edge devices Required Skills Large language models (LLMs) Model compression and quantization Network pruning and distillation On-device and edge AI optimization Deep learning frameworks (Py Torch, Tensor Flow) C++ and Python programming GPU/NPUs and hardware-aware MLPerformance profiling and benchmarking Distributed training and experimentation MLOps and deployment pipelines