Innovation Division: Applied Computer Vision Research Engineer: Visual Scene Understanding in Bay Area, CA

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OSI Engineering, Inc.
Algorithms, Computer vision, Deep learning, Computer science, Publications, PyTorch, TensorFlow, Python, Research and development, Engineering
Full Time
$105,000 - $135,000

Job Description

 Innovation Division: in Bay Area, CA

 

Summary:

Join the Innovation Division within a global automotive company that focuses on research and development of computer vision and machine learning algorithms. Move toward the understanding of scenes for next generation intelligent mobility systems, including but not limited to applications in automated driving and robotics. Our ideal candidate will have a research focused background, with knowledge of state-of-the-art methods in visual scene understanding to tackle challenging problems in multi-agent interaction modeling, explainable and interpretable behavior prediction, and video caption generation. Prefer a candidate more on engineering than research side.

 

Responsibilities:

  • Research of video-based computer vision algorithms that enables interpretation and understanding of complex traffic scenes involving high degree of interaction between road users and the environment for various driving assistance technologies.
  • Support creation of benchmark datasets for training and evaluation of algorithms, including experiment design, sensor calibration, managing data collection, creating data annotation guidelines, and managing annotation work with outside vendors.
  • Research and integration of software systems and architectures necessary to realize research prototypes.
  • Develop and evaluate metrics to verify reliability of proposed algorithms.
  • Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
  • Support the scientists in creating the publications/ patents/ prototypes.

 

Required Skillset:

  • M.S. in computer science, electrical engineering, or related field (industry experience is not required).
  • Prefer more research engineering skills with knowledge and background in the field to read papers/ articles and implement them.
  • Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
  • Strong familiarity with machine learning techniques pertaining to visual scene understanding.
  • Familiarity with scene modeling and interpretation using spatiotemporal graphs, scene graphs, graph convolution networks, or similar graphical modeling techniques.
  • Experience in open-source Deep Learning frameworks such as TensorFlow or Pytorch.
  • Highly proficient in software engineering using C++ and Python.

 

Bonus:

  • Hands-on experience in handling multi-modal sensor data.
  • Strong publication record in computer vision or machine learning.

 

Location: San Jose, CA (Hybrid schedule, relocation assistance available for candidates outside of the Bay Area, CA)

Type: Fulltime



Company Information

OSI Engineering is a leading talent acquisition and services company, building powerful IT and Engineering development teams to meet speed-to-market demands across the US. We develop, implement and manage workforce solutions through every stage of the product lifecycle, from early application development through final production, delivering the highest-level technology professionals. Our capabilities include technical staff augmentation, managed service programs and resource planning solutions.

With over 20 years of experience, OSI’s technical expertise spans the software stack from the firmware layer up to the user interface. We deliver dynamic and diverse teams for IT Services, Networking Data Services, Cloud Infrastructure and Services, Big Data, Mobile Hardware and Applications, Internet of Things (IoT), Connected Car, Enterprise Information Security and Data Science. Our quality-focused approach to talent acquisition and services helps our clients successfully launch their concepts and products that change the world.

Dice Id : 10365912
Position Id : 7427677
Originally Posted : 10 months ago

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