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Qualcomm Auto AI Systems Engineer 
India, Karnataka, Bengaluru 
57685879

23.06.2024

Job Area:

Engineering Group, Engineering Group > Systems Engineering

Knowledge of machine learning algorithms, especially related to automotive use-cases (autonomous driving, vision and lidar processing ML algorithms) are necessary.

Research experience with development of efficient networks, various Neural Architecture Search (NAS) techniques, network quantization and pruning is an added plus.

Strong communication and interpersonal skills are required and must be able to work well with various horizontal AI teams.

Preferred Qualifications:

  • PhD in related field with 1+ years of relevant experience, master’s with 3+ years, or Bachelor of engineering with 4+ years of relevant experience.

  • Good at software development with excellent analytical, development, and problem-solving skills.

  • Strong understanding of Machine Learning fundamentals

  • Hands-on experience with deep learning network design and implementation. Ability to define network from scratch in PyTorch, ability to add new loss function, modify network with torch.fx. Adept at version control system like GIT.

  • Experience in neural network quantization, compression, pruning algorithms.

  • Experience in deep learning kernel/compiler optimization

  • Strong communication skills

Minimum Qualifications:

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

Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.

PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

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.