AI/ML framework Staff Engineer

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Systems Engineering

General Summary:

Looking for “ML framework and AI compiler Engineer” responsible for

• Designing, implementing, and deploying machine learning models using PyTorch
• Focusing on backend infrastructure and system architecture. 
• Responsibilities often include developing framework, integrating with other AI tools, and ensuring scalability and reliability. 

Here's a more detailed breakdown of what you might see in such a job description:

Key Responsibilities:

• Model Development and Deployment: Designing, building, and deploying AI models, particularly those leveraging PyTorch for deep learning. 
• Backend Infrastructure: Developing and maintaining the backend systems that power AI applications, including data ingestion, processing, and storage. 
• System Architecture: Designing scalable and high-performance backend architectures to handle AI workloads. 
• Model Optimization: Optimizing model performance for speed, accuracy, and resource efficiency. 
• Integration: Integrating AI models with other systems and applications. 
• API Development: Creating and maintaining APIs for communication between frontend and backend components. 
• Data Handling: Managing data ingestion, preprocessing, and storage for AI training and inference. 
• Collaboration: Working with data scientists, product managers, and other engineers to bring AI solutions to life. 

Tools, Technologies, Skills and Programming:

• C, C++: Strong programming capability using advanced techniques to design and develop AI compilers and backends.
• Scripting: Strong expertise in Python with design, develop, release and maintain projects.
• AI Frameworks: Familiarity with other AI frameworks like PyTorch, TensorFlow, Hugging Face, etc. 

• Machine Learning Knowledge: Understanding of machine learning principles and algorithms starting Computer vision to large language models and continuously update to new trends.
• Expertise to deep learning accelerator programming (GPU, NPU). Any parallel programming experience (Like CUDA, OpenCL, MKLDNN ..etc) is a plus.
• Experience with deep leaning compilers like Glow, TVM …etc is a plus.

Minimum Qualifications:

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

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