Staff Deep Learning Engineer


  • Engineer
  • Engineering

Job Description

Senior/Staff Deep Learning Engineer
Our client is looking for a Senior/Staff Deep Learning Engineer to join their team. You will be helping the team build and develop algorithms and models on their embedded platforms. You will also be involved in real time analysis and help improve cycles of DL models.

  • 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

  • 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

Note: Any pay ranges displayed are estimations. Actual pay is determined by an applicant's experience, technical expertise, and other qualifications as listed in the job description. All qualified applicants are welcome to apply.

Yoh, a Day & Zimmermann company, is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Visit to contact us if you are an individual with a disability and require accommodation in the application process.