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QT Technologies Ireland Limited
Job Area
Engineering Group, Engineering Group > ASICS Engineering
General Summary
- Job Description
Role Overview: Join Qualcomm's NPU Architecture team as a Machine Learning Engineer specializing in PyTorch/C++ development. In this role, you will create and optimize critical technologies for our compiler, quantization processes, ML workloads, and performance optimizations. You will also collaborate directly with strategic customers to deliver impactful solutions, shaping the future of energy-efficient ML technology. Your work will empower the world’s lowest-power ML solution, deployed in more devices globally than any other.
Key Responsibilities
- Develop and enhance ML compilers using PyTorch and C++ tailored for Qualcomm’s Neural Processing Unit (NPU) architecture.
- Design and implement advanced quantization techniques to improve model efficiency and accuracy.
- Optimize ML workloads for deployment across diverse devices, ensuring top-tier performance and energy efficiency.
- Work directly with strategic customers to address specific challenges and deliver tailored ML solutions.
- Collaborate with architecture and software engineering teams to integrate cutting-edge ML technologies into Qualcomm platforms.
- Research, prototype, and implement innovative solutions in ML compiler design and system-level optimizations.
- Evaluate and debug ML performance to identify and resolve bottlenecks in complex workflows.
- Create thorough technical documentation to share knowledge and advancements with the team.
- Qualifications:
- Bachelor’s or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related discipline.
- Strong expertise in PyTorch and C++ programming.
- Experience with ML workload analysis, compiler development, and quantization techniques.
- Familiarity with deep learning frameworks such as TensorFlow or ONNX is a plus.
- Proven track record of solving complex performance and efficiency challenges in hardware-aware ML solutions.
- Ability to work collaboratively with strategic customers and deliver impactful results.
- Excellent analytical skills and ability to thrive in a high-performance team environment.
- Experience with ML model deployment on hardware accelerators such as GPUs, TPUs, or NPUs.
- Understanding of system-level architecture and low-level programming.
- Contributions to ML research or publications in relevant fields are an advantage.
Minimum Qualifications
- Bachelor's degree in Science, Engineering, or related field and 2+ years of ASIC design, verification, validation, integration, or related work experience.
Master's degree in Science, Engineering, or related field and 1+ year of ASIC design, verification, validation, integration, or related work experience.
OR
PhD in Science, Engineering, or related field.
- References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers.
Key Skills
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