Machine Learning Engineer (with Computer Vision experience)
Dallas/Fort Worth area LOCAL ONLY (Remote role with some onsite work)
Long term contract
Summary
We're looking for an incredible Senior Computer Vision Machine Learning Engineer (specifically
work on camera-related tasks) to create computer vision models that will power our computer
vision systems. Our autonomous robots take millions of pictures every day and the computer vision
solutions will help identify when products are out of stock, where items are located, if prices are
correct, and so much more. Our computer vision systems also detect items in shopping carts and
improve member exit experiences
What You'll Do
• Camera and other sensors selection, installation and support
• Evaluating and selecting appropriate cameras and sensor hardware based on performance,
cost and reliability
• In-club visit and testing
• Camera testing and Aruco testing
• System design and deployment
• Designing the layout and placement of cameras and sensors within the store to ensure
optimal coverage and data capture
• Camera parameter testing
• Involves defining and testing the specifications for the camera such as resolution, frame
rate, pixel depth, exposure time etc.
• Camera calibration and management pipeline
• Developing and implementing robust camera calibration procedures, including intrinsics
and extrinsic calibration
• Maintaining calibration accuracy over time by implementing automated recalibration
procedures or monitoring calibration drift
• Sensor fusion using multiple sensors (camera, lidar, weight scale, RFID)
• Data Annotation and Model Optimization
• Build annotated datasets from collected images/videos for model training and evaluation.
• Camera calibration model optimization
• Semi supervised annotations
• Camera monitoring
• Designing and implementing a monitoring system to track the health and performance of
the camera and sensor network.
• Monitoring camera image quality, calibration parameters, sensor data streams and system
latency
• Developing alerts and notifications for potential issues such as camera malfunctions,
calibration drift or sensor failures
• Creating tools for visualizing sensor data and calibration parameters to aid in diagnostics
and troubleshooting
• Privacy and Compliance
• Implement video anonymization techniques to protect customer privacy.
• Ensure that camera installations and data processing comply with relevant legal and
regulatory requirements.
• Research and development of computer vision and machine learning algorithms for object
detection, recognition, segmentation, and tracking
• Design, implement and deliver computer vision software systems to facilitate retail business
• Build scalable solutions to some of the challenging recognition problems in computer vision
and continuously improve performance of existing algorithms
• Drive the design and development of computer vision algorithm and software applications
implemented on cloud or edge infrastructures
• Maintain substantial knowledge of state-of-the-art principles and theories related to computer
vision
Qualifications
• Proficiency in coding (Python)
• 5 years' experience in building Computer vision/Machine Learning based models in a
professional environment
• Master degree with 3-year industrial experience or PhD degree with 1-year industrial experience
• Live in or be willing to relocate to Dallas-Forth Worth (DFW) area required
• Overtime work acceptance (work shift on the next day)
• Electrical Engineering, Mechanical Engineering, Optics fields/major
• Meiy hands-on experience with camera and Lidar is preferred
• Proficiency in computer vision and deep learning algorithms such as object detection, image
classification, image segmentation, and video analysis
• Strong understanding of probability and statistical models (generative and descriptive models)
• Ability to run experiments scientifically and analyze results
• Ability to effectively communicate technical concepts and results to business audiences in a
comprehensive manner
• Ability to collaborate effectively across multiple teams and stakeholders, including analytics
teams, development teams, product management and operations
