Company
Qualcomm India Private Limited
Job Area
Engineering Group, Engineering Group > Systems Engineering
General Summary
Qualcomm Bangalore AI Research is looking for world-class engineers in general domain of machine learning and more specifically deep learning for computer vision and image processing tasks. Our work is at the confluence of classical image processing and cutting edge machine learning technologies. Active areas of research include low power embedded AI on edge devices, improving image quality through hybrid real time processing, AI based personalization and recommendation systems, generative models and multi-modal fusion. The team comprises highly skilled and motivated professionals building advanced machine learning technology, best-in-class solutions, and model optimization tools enabling state-of-the-art network inferences on-device with limited power, memory, and computation.
Members of our team enjoy the opportunity to participate in cutting edge research while simultaneously contributing technology that will be deployed worldwide in our industry-leading devices.
Roles & Responsibilities
You will be part of a multi-disciplinary talented team working on on-device AI research, development and end-to-end prototyping of given use-case for camera ISP. Collaborate in a cross-functional environment spanning hardware, software and systems. See your design in action on industry-leading chips embedded in the next generation of smartphones, augmented reality headsets, autonomous vehicles, robotics, and IOT devices.
Key job responsibilities may include a subset of the following:
- Develop learnable image signal processing (ISP) pipeline for image reconstruction and classification tasks
- Develop objective metrics and methodologies to measure image quality.
- Develop machine learning algorithms for advanced imaging features (low-light, next-generation sensors, vision and scene understanding etc.)
- Work on training strategies and supporting deployment and commercialization for the machine learning features
- Work on system and algorithmic design changes to improve machine learning inference speed
- Work on quantization and low rank adaptation strategies
- Drive innovative research ideas and develop prototype in collaboration with other researchers and engineers.
- Stay abreast with the latest SOTA and actively shape latest research in the field.
- Stay passionate at execution.
- Contribute to purposeful innovation.
- Engage with leads and stakeholders across business units to translate research into business impact.
Minimum Qualifications
- Master's degree in Computer Science, Electrical/Electronics Engineering or related Engineering field with 3+ years of related work experience in AI Research, Image Processing, Software & Systems Engineering.
- Strong background in image and signal processing, statistics, and data analysis.
- Strong programming skills and working experience in C/C++ and Python.
- Working knowledge of image quality and associated metrics.
- Working experience in machine learning and deep network architectures
- Working experience with machine learning framework/packages (e.g, PyTorch, TensorFlow)
Additional Qualifications (Preferred)
- PhD in Computer Science, , Electrical/Electronics Engineering or related Engineering field with active experience in AI Research and Image Processing.
- Background in color science, and image signal processor pipelines.
- Prior work experience with Object detection/classification/tracking, Recommendation Systems, Human Aware AI and RAW / RGB domain ISP Tasks
- Exposure to hardware and systems architecture for power, performance, accuracy trade-offs
- Prior work experience with on-device AI model optimization, federated learning, RL, IL.
Keywords: Computer Vision, Image Processing, ISP, Image Quality Metrics, Model Optimization, Deep Learning, Machine learning.
Minimum Qualifications
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field.
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