Job Overview

Qualcomm is hiring a Machine Learning Tools Engineer in Hyderabad to work on software infrastructure for on-device Generative AI. The role is part of a team developing and commercializing the Qualcomm AI Runtime SDK for Qualcomm SoCs, with a focus on making advanced AI models run efficiently on power-conscious edge hardware.

This position is aimed at experienced software engineers who understand both modern Generative AI workloads and low-level systems development. You will work with large language, vision, and multimodal models and help improve the software stack that enables these models to execute efficiently on Qualcomm platforms.

The work combines C and C++ software engineering, AI inference optimization, hardware acceleration, operating system concepts, and Python scripting. You will also investigate new GenAI developments and apply them to edge computing, where performance, memory usage, latency, and power efficiency are important.

Key Responsibilities

• Develop and enhance software components for the Qualcomm AI Runtime SDK used on Qualcomm SoCs.
• Build and maintain large-scale C and C++ software stacks using sound software engineering practices.
• Improve AI inference performance for large language, vision, and multimodal models on edge devices.
• Study model execution requirements and optimize algorithms for heterogeneous hardware accelerators.
• Work with CPU, GPU, and NPU capabilities to improve inference efficiency.
• Apply knowledge of Generative AI architectures, including attention mechanisms and key-value caching.
• Investigate performance bottlenecks and develop practical solutions for AI workloads.
• Work with floating-point and fixed-point representations and apply quantization concepts where appropriate.
• Use Python for scripting, automation, experimentation, and engineering support tasks.
• Analyze complex software and system issues and contribute to debugging and performance improvement.
• Collaborate with software, hardware, architecture, and other engineering teams on system-level solutions.
• Evaluate emerging GenAI techniques and understand how they can be deployed effectively at the edge.
• Contribute to the development and commercialization of software supporting AI inference on Qualcomm chipsets.

Required Skills

Strong C and C++ programming experience is central to this position. Candidates should understand object-oriented software development, design patterns, operating system concepts, and the development of substantial software systems.

A strong understanding of Generative AI is also required. Candidates should be familiar with Large Language Models, Large Vision Models, Large Multimodal Models, and important model building blocks such as self-attention, cross-attention, and key-value caching.

Experience optimizing algorithms for AI hardware accelerators is important. Candidates should understand how workloads can be adapted for CPU, GPU, and NPU architectures and how numerical representations affect model performance and efficiency.

Knowledge of floating-point and fixed-point computation, along with quantization techniques, is required for working on efficient AI inference systems.

Python scripting skills are expected for engineering automation and supporting development activities. Strong analytical and debugging abilities are important because the role involves identifying performance and system-level issues in complex AI software stacks.

Preferred Skills

Experience with SIMD processor architecture and system design can be valuable, particularly for engineers working on performance-sensitive AI workloads. A background in kernel development for SIMD architectures is also advantageous.

Familiarity with Linux and Windows environments is preferred. Candidates may also benefit from experience with modern AI and inference frameworks such as llama.cpp, MLX, and MLC.

Knowledge of PyTorch, TFLite, and ONNX Runtime is useful for understanding model frameworks and inference workflows. Experience with parallel computing and technologies such as OpenCL and CUDA is an additional advantage.

Education

The position requires a Bachelor's or Master's degree in Computer Science or an equivalent discipline. The broader Qualcomm qualification criteria also recognize relevant engineering, information systems, or computer science education pathways.

Experience

The role requires 6 or more years of relevant software development experience. Candidates should be able to demonstrate substantial hands-on work in software engineering, preferably involving C or C++, AI inference, performance optimization, systems software, or related technical areas.

The strongest applications will demonstrate practical experience working close to hardware or performance-sensitive software, along with an understanding of modern Generative AI models and their deployment requirements.

Required Technologies

Core technologies and concepts for this role include C, C++, Python, Generative AI, LLMs, LVMs, LMMs, Transformers, self-attention, cross-attention, key-value caching, floating-point computation, fixed-point computation, quantization, CPU, GPU, NPU, SIMD architectures, operating systems, and object-oriented programming.

Relevant AI and software frameworks include llama.cpp, MLX, MLC, PyTorch, TFLite, and ONNX Runtime. Parallel computing technologies mentioned in the role include OpenCL and CUDA. Linux and Windows are also relevant development environments.

Soft Skills

The role requires strong analytical thinking and a disciplined approach to debugging complex software and performance problems. Engineers should be comfortable exploring technical details, forming hypotheses, testing solutions, and communicating findings clearly.

Good verbal, written, and presentation skills are important because the work involves collaboration across different engineering disciplines. Candidates should also be able to work effectively with globally distributed teams and balance different technical priorities.

Curiosity and a willingness to keep learning are valuable in this role because Generative AI, model architectures, and edge inference technologies continue to evolve rapidly.

Benefits of Working in this Role

This role provides hands-on exposure to the intersection of Generative AI, systems software, and specialized hardware acceleration. Engineers can work on technologies that help bring advanced AI capabilities directly to edge devices instead of relying entirely on cloud connectivity.

The position also offers opportunities to deepen expertise in C and C++, AI inference optimization, heterogeneous computing, model quantization, SIMD architectures, and modern GenAI frameworks. Working across software and hardware domains can help build strong system-level engineering skills.

Work Mode

The job description does not specify a remote or hybrid arrangement. This is a full-time position based in Hyderabad.

Location

Hyderabad, Telangana, India.

Who Should Apply

This opportunity is suitable for experienced software engineers with 6 or more years of development experience who have strong C or C++ skills and an interest in Generative AI inference.

Candidates should highlight experience with performance optimization, AI accelerators, systems programming, operating systems, kernel development, SIMD architectures, or other low-level software work. Experience with LLMs, LVMs, LMMs, Transformers, quantization, or edge AI deployment is especially relevant.

Applicants with knowledge of PyTorch, TFLite, ONNX Runtime, llama.cpp, MLX, MLC, OpenCL, or CUDA should clearly describe how they have used these technologies. Practical examples of debugging and improving AI inference performance can make an application stronger.

Career Growth

Experience in this role can support career paths such as Senior Software Engineer, AI Inference Engineer, Machine Learning Systems Engineer, Edge AI Engineer, AI Runtime Engineer, Performance Engineer, Systems Software Engineer, or Technical Lead.

The combination of Generative AI knowledge and low-level systems expertise can also help engineers move toward specialized roles involving AI compilers, inference runtimes, hardware acceleration, embedded AI, or large-scale AI platform development.

Application Advice

Focus your resume on measurable engineering contributions rather than listing technologies without context. Describe C or C++ projects involving performance, systems, hardware acceleration, inference, kernels, or large software stacks.

Clearly mention your experience with Generative AI models and explain whether you have worked with LLMs, vision models, multimodal models, Transformers, attention mechanisms, quantization, or inference optimization.