Machine Learning Engineer
Confirmed live in the last 24 hours
Santa Monica, CA, USA
Experience Level
Desired Skills
Computer Vision
Data Science
Data Structures & Algorithms
AI & Machine Learning
  • Master's degree, or equivalent, in Computer Science, Data Science, or related field plus:
  • Two (2) years of Machine Learning, Data Science, or related experience: researching and implementing appropriate machine learning applications; building machine learning models; applying transfer-learning to all new models; developing analytical tools to analyze model performance and data accuracy; performing statistical analysis and fine tuning applied algorithms/models; designing/re-designing requirements based on cues obtained from model outputs; building custom evaluation metrics and data pipelines; visualizing and integrating APIs to assist in overall processes; and documenting model performance and outcomes to drive business decisions. Telecommuting Permissible
  • Serve as part of ZEFR's engineering team to design and build large-scale applications and systems to acquire, process, and store multi-terabytes of YouTube, Facebook, and other social media data
  • Research and implement machine learning tools and applications needed to cater to ZEFR's business requirements. Implement machine learning infrastructure to 'learn from' and understand hundreds of millions of videos through 'big data' content analysis and extraction of useful (e.g., licensed content) data
  • Design, test, develop, implement, and deploy novel solutions for integrating data collected from a multitude of sources by leveraging the latest in data science, machine learning and computer vision
  • Contribute to ZEFR's deployment of next generation machine learning and vision systems, pipelines and models, based on open-source platforms, to enhance ZEFR's data structure management, and algorithm and software designs
  • Contribute to the development of ZEFR's software and analyzing complex data for the large-scale distributed systems, including designing analytical frameworks and machine learning models to facilitate the expansion of key web-based applications for processing large amounts of data
  • Manage data compilation and integration operations shared over the complex data infrastructure, and ensure that data is stored and organized efficiently to allow fluid I/O workflows
  • Collaborate with the Operations Team to design or re-design machine learning requirements based on cues obtained from model outputs. Document and communicate key findings, model performance, and outcomes to team members to drive business decisions
  • Architect systems and build tools to enable ZEFR to deploy, evaluate, and iterate on product deliveries seamlessly and quickly