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Computer Vision Engineer

San Francisco, CA 94016

Posted: 08/16/2023 Employment Type: Direct Hire Job Number: 22701 Workplace Type: Hybrid

Job Description

Compensation: $200k plus equity
Summary of Responsibilities:
  • Develop computer vision algorithms for object detection, tracking, semantic segmentation, and classification.
  • Build and train deep learning models to enable complex urban scene perception and real-time analysis.
  • Participate in end-to-end development: from problem statement, data aggregation, and annotation, through model design, experiments, and training, to the deployment of the optimized model on embedded platforms and iterative improvement automation.
  • Automation of improvement cycles of DL models.

Summary of Qualifications:
  • BS, MS, or Ph.D. in Robotics, Machine Learning, Computer Science, Electrical Engineering, or a related field.
  • Must have 8+ years of Expertise in deploying real-world applied computer vision (including deep learning models) on edge devices.
  • Strong Python programming and software design skills, knowledge of C++.
  • Familiarity with standard tools and libraries, e.g. Pytorch, OpenCV, Tensorflow, MLflow.
  • Proven track record - significant industry experience and/or publications at venues such as ICRA, RSS, IROS, or CVPR.
  • Experience in automated data annotation.

Bonus Qualifications:
  • Multi-task models training.
  • Semi-supervised DL models training on video data.
  • Experience in design of multi-modal DL models with temporal context and geometrical constraints.
  • Understanding of optimization of DL models and deployment on embedded platforms such as the Nvidia Jetson.
  • Experience in CUDA programming, low-level edge model optimization using e.g. TensorRT and similar tools.
  • Experience in designing automated machine learning pipelines.

We look forward to reviewing your application. We encourage everyone to apply - even if every box isn’t checked for what you are looking for or what is required.

PDSINC, LLC is an Equal Opportunity Employer.

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