Company:

Qualcomm India Private Limited:

Job Area:

Engineering Group, Engineering Group > Systems Engineering

General Summary:

Qualcomm XR Research India is rapidly expanding to offer state of the art and futuristic XR solutions that would shape the future of Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) use cases. At XR ML systems team, we are augmenting our XR capabilities from traditional sensing modalities like Vision and IMU to novel modalities like Speech and Language to create better user experiences. We are looking for a Lead-Senior Engineer, with a very strong background in the state-of-the-art Large Language Models and Multimodal Deep-learning Techniques. We prefer candidates with a strong academic background in AI/ML/DL areas with a significant industrial experience in innovating, implementing and packaging these algorithms on real-world AI products.

Responsibilities:

As a dependable Individual Researcher in this role, you will be holding the following responsibilities.

• Quickly comprehending SOTA algorithms on LLMs and their derivatives, implementing on Linux PC, migrating to Qualcomm HW, Profiling and Optimizing those algorithms

• Tactical leadership in problem-solving through innovating simple but effective LLM-based solutions for pushing the boundaries of our XR solutions and products.

• Systems thinking for dissecting any XR use-case to a set of AI/ML/DL algorithms and quickly building prototypes which are both accurate and efficient in Python and/or C++.

• Quickly ramping up on Qualcomm ML tools like SNPE, QNN SDK and AIMET and using these tools to analyze and improve the performance of external and home-grown ML/DL algorithms on Qualcomm devices.

• Strong Ownership on delivering high quality results and meeting project timelines by proactively unblocking constraints by interacting with key stakeholders in SW, Algorithms and Tooling teams.

• Periodically communicating the progress to key-stake holders through oral and written methods, seek feedback and instrument solutions to address the gaps.

Minimum Qualifications:

• 4+ years of hands-on experience in Deep Learning research and development, with a Master’s degree in electrical engineering, information systems, computer science, or related field.

• 2+ years of Hands-on experience in developing LLM-related algorithms that were deployed in real-world AI products;

• Very good proficiency in transformer-based DL algorithms and programming languages that include Python and C

• Very good proficiency and hands on experience in State-of-the-art DL frameworks like Py Torch, ONNX and Tensorflow.

• Very good proficiency and a strong theoretical background in all AI/DL/ML concepts for ML-system design, problem-formulation, training and testing methodologies and continuous improvement.

• Strong communication skills and inter-personal skills to work effectively in a team.

Preferred Qualifications:

• 2+ years of industrial experience in AI/ML/DL algo development with a PhD degree in computer science, electrical engineering and information systems from top-tier institutions.

• Proven expertise in data-curation and training of LLMs, Optimizing LLMs for resource constrained environments like mobile phones, mapping LLMs on to embedded platforms, Personalization/Customization of LLMs or distributed processing of LLMs.

• Hands on experience in transformer optimization techniques for training and inference.

• Proficiency in Generative and Multimodal AI models not limited to LLMs

• Publications in Top-TIER AI/ML conferences like CVPR, ECCV, ICLR, ICML or Neurips is a huge plus.

• Proficiency in C++ and Embedded SW Development.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. OR
  Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
  OR
  PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.

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