Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Software Engineering

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what’s possible to enable next-generation experiences and drive digital transformation toward a smarter, more connected future.

As a Staff Software Engineer in the Machine Learning Group, you will design and build high-performance, scalable software systems that enable efficient execution of state-of-the-art machine learning and generative AI workloads on Snapdragon platforms for Windows and Linux.

This role focuses on the development of the Qualcomm Orchestrator SDK and associated tooling, enabling AI orchestration, agentic workflows, and optimized inference across heterogeneous compute resources (CPU, GPU, NPU, DSP). You will act as a senior technical contributor with ownership over architecture, platform enablement, and cross-team technical execution.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.

• 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Key Responsibilities

• Design, develop, and maintain AI orchestration frameworks, runtime engines, and SDK tools for Windows and Linux platforms.

• Enable execution of modern ML and GenAI workloads, including multi-model and agentic workflows, on Snapdragon-based systems.

• Architect and implement workflow scheduling, execution graphs, resource management, and model coordination across heterogeneous hardware.

• Drive SDK feature development, platform enablement, and performance improvements for Windows and Linux.

• Optimize ML inference pipelines for latency, throughput, memory efficiency, and power consumption.

• Collaborate closely with AI software, platform, hardware, and tools teams to deliver end-to-end solutions.

• Define and influence SDK architecture, public APIs, and developer-facing interfaces.

• Provide technical leadership through design reviews, code reviews, and mentorship of other engineers.

• Make high-impact technical decisions affecting multiple projects and stakeholders.

Minimum Qualifications

• 8+ years of industry experience in software engineering.

• 5+ years of system-level software development on Linux and/or Windows platforms.

• Strong proficiency in C/C++ for production-quality, performance-critical software.

• Solid understanding of data structures, algorithms, and modern software design principles.

• Experience with Windows system and application development, including:

  • Build systems and toolchains

  • DLLs and shared libraries

  • Application, framework, and runtime integration within the Windows stack

• Ability to work independently with minimal supervision in complex and ambiguous problem spaces.

• Strong verbal and written communication skills, with the ability to convey complex technical concepts to engineers and senior stakeholders.

Preferred Qualifications

Platform & Systems Expertise

• Windows OS development: 5+ years of experience in Windows system software, core OS applications, framework integration, or low-level platform components.

• Strong experience developing cross-platform software for Windows and Linux using C/C++.

• Expertise with build and packaging systems such as CMake, Ninja, Bazel, and MSBuild.

• Experience with runtime systems, plugin architectures, and modular SDK design.

Machine Learning & GenAI Systems

• Hands-on experience deploying and orchestrating LLMs, LMMs, LVMs, and LoRA-based adaptations.

• Experience with ML inference and runtime frameworks, such as:

  • SNPE, QNN, LiteRT, ExecuTorch, MLIR, ONNX Runtime

• Understanding of model graph execution, runtime optimization, and scheduling.

• Familiarity with model optimization techniques including quantization, pruning, and graph transformations.

Performance & Hardware Acceleration

• Experience optimizing software for heterogeneous compute architectures (CPU, GPU, NPU, DSP).

• Strong understanding of parallelism, memory management, and low-latency system design.

• Exposure to GPU or accelerator programming concepts and performance analysis tools.

Software Engineering Excellence

• Experience using Python and/or Java for tooling, automation, testing, or orchestration layers.

• Knowledge of CI/CD pipelines, automated testing, and release engineering for SDKs.

• Advanced debugging skills across system, runtime, and application layers.

• Understanding of secure software development practices, ABI/API stability, and backward compatibility.

Data & Infrastructure

• Experience with data storage and retrieval systems, including:

  • Vector databases (Faiss or similar)

  • SQLite, MongoDB, and other NoSQL solutions

• Familiarity with logging, telemetry, and observability in large-scale systems.

Leadership & Technical Depth

• Demonstrated ability to contribute to commercial-grade software architecture and long-term platform strategy.

• Up-to-date knowledge of trends in:

  • Agentic AI systems

  • Generative AI/ML inference

  • ML systems and runtime optimization

• Strong ownership, self-motivation, and ability to lead through influence rather than authority.

Education Requirements

Required

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.

Preferred

• Advanced degree (Master’s or PhD) in a relevant discipline.

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