Machine Learning Engineer
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.
What you’ll do:
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.
What we’re looking for:
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.
Zefr is an equal opportunity employer that embraces diversity and inclusion in the workplace. We are committed to building a team that represents a variety of backgrounds, skills, and perspectives because we know this only makes us better. We strongly encourage women, persons of color, LGBTQIA+ individuals, persons with disabilities, members of ethnic minorities, foreign-born residents, and veterans to apply even if you do not meet 100% of the qualifications.
Telecommuting is permissible for this role.
Benefits (for US based employees):
Medical, dental, and vision insurance with FSA options
Company-paid life insurance
Paid parental leave
401(k) with company match
Professional development opportunities
14 paid holidays off
In-office, hybrid, and fully-remote work options available
Shorter work days every other Friday
In-office lunches and lots of free food
Optional in-person and virtual events (we like to celebrate!)
Compensation (for US based employees):
The anticipated base salary for this position is between $180,000 and $200,000. Within the range, individual pay is determined by factors such as job-related skills, experience, and relevant education or training. If your compensation expectations fall outside of this range, it may still be worth having a conversation.