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1 month ago

San Diego, United States Qualcomm Full time

The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive market. Qualcomm’s Cloud AI 100 accelerators are currently deployed at AWS / Cirrascale Cloud and at several large organizations. We are rapidly expanding our ML hardware and software solutions for large scale deployments and are hiring across many disciplines.

We are seeing to hire for multiple machine learning positions in the Qualcomm Cloud team. In this role, you will work with Qualcomm's partners to develop and deploy best in class ML applications (CV, NLP, GenAI, LLMs etc) based on popular frameworks such as PyTorch, TensorFlow and ONNX, that are optimized for Qualcomm's Cloud AI accelerators. The work will include model assessment of throughput, latency and accuracy, model profiling and optimization, end-to-end application pipeline development, integration with customer frameworks and libraries and responsibility for customer documentation, training, and demos.

  • This candidate must possess excellent communication, leadership, interpersonal and organizational skills, and analytical skills.
  • This role will interact with individuals of all levels and requires an experienced, dedicated professional to effectively collaborate with internal and external stakeholders.
  • The ideal candidate has either developed or deployed deep learning models on popular ML frameworks.
  • If you have a strong appetite for technology and enjoy working in small, agile, empowered teams solving complex problems within a high energy, oftentimes chaotic environment then this is the role for you.

Key Responsibilities:

  • Key contributor to Qualcomm’s Cloud AI GitHub repo and developer documentation.
  • Work with developers in large organizations to
    • Onboard them on Qualcomm’s Cloud AI ML stack
    • improve and optimize their Deep Learning models on Qualcomm AI 100
    • deploy their applications at scale
  • Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning.
  • Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator.
  • Optimize LLM/GenAI workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems.
  • Partner with product management, hardware/software engineering to highlight customer progress, gaps in product features etc.

Minimum Qualifications:

  • Masters's degree in Computer Science, Computer Engineering, electrical engineering or relevant technical field, or equivalent practical experience.
  • 5+ years of deep learning model development or deployment experience on CPUs/GPUs/ASICs.
  • Excellent C/C++/Python programming and software design skills, including debugging, and performance analysis.
  • Proven communications skills and demonstrated experience influencing cross functional teams.

Preferred Qualifications:

  • Hands-on experience running deep learning models on popular ML frameworks such as PyTorch, TensorFlow, ONNX, Caffe2
  • Experience developing software solutions that run in Linux environments including containers (docker, K8s, Rancher etc) and virtual machines.
  • Experience with Source code and configuration management tools, git knowledge is required.