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Machine Learning Engineer, Cloud Computing

2 months ago

San Diego, United States Nutanix Full time

The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions aimed at data centers. We are seeking ambitious, bright, and innovative engineers. Job activities span the whole product life cycle from early design to commercial deployment. The environment is fast-paced and requires cross-functional interaction daily so good communication, planning and execution skills are a must.

Qualifications:
  • 2+ years of Software Engineering experience. Strong object-oriented design and development skills.
  • Extensive programming experience using C/C++ & Python.
  • Knowledge of neural networks, with hands-on experience using ML frameworks such as PyTorch.
  • Knowledge of Large Language Models (LLMs), CNN etc.
  • Hands-on experience with code generation implementation/optimization leveraging compiler frameworks such as LLVM, GCC, or machine learning compilers such as TVM, Glow, XLA or TensorFlow.
  • Experience with Source Code and Configuration management tools, such as Git.
  • Strong debugging and analysis skills, for root causing complex issues.
  • Knowledge Qualcomm Hexagon DSP is a plus.
  • Experience developing embedded software, preferably on-device ML.
  • Previous experience working in an Agile environment and collaborating with multi-disciplinary teams.

Principal Duties and Responsibilities:

  • Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
  • Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions.
  • Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development.
  • Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.
  • Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers.
  • Conducts complex experiments to train and evaluate machine learning models and/or software independently.
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