Description:

The Computer Vision Engineer (The Visual Intelligence Architect) will develop algorithms that enable machines to interpret and make sense of visual data.
This role involves creating computer vision systems that recognize, analyze, and respond to real-world environments.
The engineer will work with multidisciplinary teams to build solutions that process visual information, detect objects, and make real-time decisions.
Key responsibilities include designing, developing, and optimizing algorithms for object detection, tracking, recognition, and segmentation using deep learning and traditional vision techniques.
The engineer will implement and train machine learning models using frameworks like TensorFlow and PyTorch to interpret and classify visual data.
Integration of vision systems into robotics and automation platforms is essential, ensuring seamless data flow for responsive performance.
Calibration and testing of cameras, sensors, and optics will be performed to ensure precise data capture and interpretation.
The engineer will optimize algorithms for real-time processing on edge devices and embedded systems, focusing on high-speed, low-latency performance.
Collaboration on data collection and annotation processes will be necessary to prepare labeled datasets for training models.
Continuous research on new techniques, tools, and methodologies in computer vision and machine learning will be expected to enhance system capabilities.

Requirements:

Expertise in computer vision and image processing is required, with a strong understanding of concepts like object detection, segmentation, and pattern recognition, and experience using libraries like OpenCV and scikit-image.
Proficiency in deep learning and machine learning frameworks such as TensorFlow, PyTorch, or Keras for developing and training vision models is necessary.
Programming skills in Python and C++ are essential, with experience in ROS (Robot Operating System) considered a plus.
Familiarity with sensors and hardware calibration, including camera calibration and stereo vision, as well as experience with LIDAR and depth sensors, is required.
Strong analytical and problem-solving skills are necessary for troubleshooting algorithms and optimizing performance in real-world conditions.
A Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field is required, with equivalent experience in computer vision engineering considered.
3+ years of experience in computer vision engineering, particularly in robotics or autonomous systems, is required.
Experience with embedded or edge computing for vision applications is beneficial, and familiarity with 3D computer vision, SLAM, or multi-view geometry is a plus.

Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
Competitive vacation, sick leave, and 20 paid holidays per year are included in the paid time off policy.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs support professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources, is available.
Life insurance and short-term/long-term disability coverage are offered as part of the life and disability insurance benefits.
Confidential counseling and support services for personal and professional challenges are provided through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is available through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged for community engagement.
Employee recognition programs celebrate achievements and milestones, fostering a positive work environment.