Senior Deep Learning/Machine Learning Engineer

  • Santa Clara, CA
  • Posted 48 days ago | Updated 2 hours ago

Overview

On Site
Full Time

Skills

Natural language processing
Deep learning
Machine Learning (ML)
Open source
Quality assurance
Software development
Executive search
Training
DNN
Benchmarking
Writing
Cloud computing
PyTorch
Debugging
Python
Git
Computer hardware
Optimization
Torch
Microsoft Dynamics SL
Network
Recruiting
Strategy
FOCUS
Facebook
LinkedIn
DICE

Job Details

Our client is looking to fill the role of Senior Deep Learning/Machine Learning Engineer. This role will be hybrid and based out of the Santa Clara office.

Responsibilities:
  • Training, and deploying deep learning models for a variety of DNN tasks.
  • Optimizing and compiling models for different runtime agents including OpenVino, ONNX runtime, TensorRT, TFLite runtime, and HW.
  • Work with open-source custom models and datasets, and port open-source models to our supported runtimes.
  • Benchmarking the ported models on different runtimes and writing quality assurance code for maintenance.
  • Document and maintain all the developed models.
  • Training and deploying deep learning models for a variety of DNN tasks.
  • Optimizing and compiling models for different runtime agents including OpenVino, ONNX runtime, TensorRT, TFLite runtime, and our HW.
  • Work with open-source custom models and datasets, and port open-source models to supported runtimes.
  • Benchmarking the ported models on different runtimes and writing quality assurance code for maintenance.
  • Document and maintain all the developed models.
Required Qualifications:
  • Bachelor's degree or equivalent practical experience.
  • At least 2 years' experience in ML development: (a) training networks locally/on cloud and/or (b) deploying models in the production environment.
  • Experience with Pytorch
  • Experience with software development and debugging in Python.
  • Experience with applied machine learning.
  • Ability to write ML model definitions and training loops.
  • Familiarity with common (vision and natural language processing) datasets and how to use them.
  • Experience with Git
  • Experience with Vision models e.g. Yolov8.
  • Familiarity with machine learning hardware optimization methods such as quantization and pruning.
  • Familiarity with TFLite, ONNX or Torch Script
  • Familiarity with Runtime agents like OpenVINO, TensorRT, TFlite runtime

If you meet the required qualifications and are interested in this role, please apply today.

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Opportunity Awaits.

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