Machine Learning Engineer

ONE STOP COLLECTIBLE CORP

Los Angeles, CA, United States

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

2 years minimum

Working hours

Regular working hours

Job source

startup.jobs

Tech stack

Computer Vision Confluence Image Analysis Data Structures Python (Programming Language) Object Detection Tensorflow Pytorch Deep Learning Convolutional Neural Networks Information Technology Data Management

Job description

Develop deep learning models for prototyping and production purposes according to product feature request
Design, implement and test model experiments using major deep learning frameworks
Document experiments findings and results with supporting summary statistics for peer discussion and review (Confluence)
Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling
Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed
Conduct methodology research in deep learning to drive scalable, real-time implementation

Requirements

MS degree in computer science, engineering, or mathematics
2-3 years of relevant experience in building deep learning solutions for computer vision problems
Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch
Proficient in Python
Good CS fundamentals in data structures and algorithm
Detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged
Work well in teams and communicate ideas clearly, * PhD degree in computer science, engineering, or mathematics
3-5 years of relevant experience in building deep learning solutions for computer vision problems
Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet).
Track record of publications in CV and medical image analysis is a plus
Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus
Prior experience with medial images is a plus