ZEFR
Senior Data Scientist, Computer Vision
ZEFR, MARINA DEL REY, CA
Senior Data Scientist, Computer Vision sought by ZEFR, Inc. in Los Angeles, CA
What we do: Zefr is the global leader in brand suitability targeting and measurement across the world's largest platforms. Zefr's technology is helping to power the age of responsible marketing by putting advertisers in control of their content adjacencies based on their own unique brand safety and suitability preferences, mapped to the Global Alliance of Responsible Media's (GARM) industry standards. As an official YouTube Measurement Program Partner, Meta for Business Partner, and TikTok for Business Partner, the company leverages patented machine learning and AI technology (Cognition AI) to offer brands and agencies more precise and transparent brand safety and suitability activation and measurement solutions on scaled platforms. The company is headquartered in Los Angeles, California, with additional locations across the globe.
Duties: Design and optimize large-scale systems that ingest, process, label, index, and store vast amounts of image and video data on social media platforms like YouTube, Facebook, and TikTok. Leverage computer vision, machine learning, and deep learning concepts to design, implement, test, and deploy various machine learning and computer vision models to ZEFR's patented Cognition AI technology which will 'learn from' and understand hundreds of millions of videos through 'big data' analysis and extract useful content-related (e.g., licensed content) data that offer brands and agencies more accurate measurement solutions. Contribute to ZEFR's rapidly growing data management demands to keep the company at the forefront in providing content adjacency solutions for content owners and brands in accordance with industry standards like the Global Alliance of Responsible Media (GARM) framework. Analyze and utilize visual data by applying various Computer Vision techniques to develop software requirements and solutions. Utilize natural language and image processing algorithms to improve data analysis and cultivation. Build mathematical and statistical models to analyze data and to identify visual content. Architect a semantic search engine for image and text embeddings to enable discovery and sourcing. Scale the pipeline to enable the processing of large quantity of videos. Integrate models into a large-scale engineering system including automatic retraining and model deployment based on user feedback. Translate data requirements of stakeholders to produce well-written, clean, and predictive computer vision models, both supervised and unsupervised. Prototype creative solutions quickly, testing theories, evaluating feature concepts, and iterating the processes rapidly. Develop end-to-end machine learning pipelines for large data sets from data exploration, feature engineering, model building, performance evaluation, to online testing.
Requirements: Master's degree, or equivalent, in Data Science, Information Technology, Statistics, Mathematics, or related field plus two (2) years of data science, data engineering, software engineering, or related Experience including one (1) year of experience: utilizing deep learning for image analysis; building footprints segmentation to ensure high IoU score and data accuracy; implementing complex deep learning architectures; implementing semantic segmentation model architectures; optimizing computer vision algorithms; synchronizing parameters across multiple graphics processing units (GPUs); integrating machine learning models into real-world applications; collaborating with cross-functional teams to deliver segmentation and classification solutions; and utilizing various machine learning related technologies such as Python, C++, MxNet, and Caffe. Telecommuting permissible.
Salary: $210,000/year
To Apply: Send Resume to: Chris Dale, Director, Human Resources, ZEFR, Inc., 4101 Redwood Avenue, Los Angeles, CA, 90066 or email [redacted].
What we do: Zefr is the global leader in brand suitability targeting and measurement across the world's largest platforms. Zefr's technology is helping to power the age of responsible marketing by putting advertisers in control of their content adjacencies based on their own unique brand safety and suitability preferences, mapped to the Global Alliance of Responsible Media's (GARM) industry standards. As an official YouTube Measurement Program Partner, Meta for Business Partner, and TikTok for Business Partner, the company leverages patented machine learning and AI technology (Cognition AI) to offer brands and agencies more precise and transparent brand safety and suitability activation and measurement solutions on scaled platforms. The company is headquartered in Los Angeles, California, with additional locations across the globe.
Duties: Design and optimize large-scale systems that ingest, process, label, index, and store vast amounts of image and video data on social media platforms like YouTube, Facebook, and TikTok. Leverage computer vision, machine learning, and deep learning concepts to design, implement, test, and deploy various machine learning and computer vision models to ZEFR's patented Cognition AI technology which will 'learn from' and understand hundreds of millions of videos through 'big data' analysis and extract useful content-related (e.g., licensed content) data that offer brands and agencies more accurate measurement solutions. Contribute to ZEFR's rapidly growing data management demands to keep the company at the forefront in providing content adjacency solutions for content owners and brands in accordance with industry standards like the Global Alliance of Responsible Media (GARM) framework. Analyze and utilize visual data by applying various Computer Vision techniques to develop software requirements and solutions. Utilize natural language and image processing algorithms to improve data analysis and cultivation. Build mathematical and statistical models to analyze data and to identify visual content. Architect a semantic search engine for image and text embeddings to enable discovery and sourcing. Scale the pipeline to enable the processing of large quantity of videos. Integrate models into a large-scale engineering system including automatic retraining and model deployment based on user feedback. Translate data requirements of stakeholders to produce well-written, clean, and predictive computer vision models, both supervised and unsupervised. Prototype creative solutions quickly, testing theories, evaluating feature concepts, and iterating the processes rapidly. Develop end-to-end machine learning pipelines for large data sets from data exploration, feature engineering, model building, performance evaluation, to online testing.
Requirements: Master's degree, or equivalent, in Data Science, Information Technology, Statistics, Mathematics, or related field plus two (2) years of data science, data engineering, software engineering, or related Experience including one (1) year of experience: utilizing deep learning for image analysis; building footprints segmentation to ensure high IoU score and data accuracy; implementing complex deep learning architectures; implementing semantic segmentation model architectures; optimizing computer vision algorithms; synchronizing parameters across multiple graphics processing units (GPUs); integrating machine learning models into real-world applications; collaborating with cross-functional teams to deliver segmentation and classification solutions; and utilizing various machine learning related technologies such as Python, C++, MxNet, and Caffe. Telecommuting permissible.
Salary: $210,000/year
To Apply: Send Resume to: Chris Dale, Director, Human Resources, ZEFR, Inc., 4101 Redwood Avenue, Los Angeles, CA, 90066 or email [redacted].