Surreal Data EngineerSoftware Engineering | Redmond, WA
Come invent the future!
At Facebook Reality Labs (FRL), computer vision and machine learning (CV/ML) are vital to turbocharging our scientific explorations and generating viable paths to the consumer products people will use for decades to come - products that will literally give people super powers.
We are looking for a Data Engineer to drive managing and organization of our algorithm analysis data from our computer vision and machine learning (CV/ML) teams. This is a massive amount of data that we are collecting in order to inform and refine algorithm choices and to ensure we have the best algorithms. You'll work with world class researchers, engineers and software developers to enable a large group of people to do ground breaking work in their fields.
* Create and implement reports and dashboards for ongoing research into various projects, such as SLAM, relocalization, anonymization, mapping * Propose, collect data, analyze and report on deep investigations into algorithm performance/architecture proposals * Explore and analyze current data for insights into areas of improvement of current solutions * Develop and manage data set processes across the team and across the organization at large * Assist in creation and maintenance of evaluation pipeline * Collaborate in a team environment across multiple scientific and engineering disciplines * Spread knowledge and best practices across the team, enabling teams to do local analysis and build smarter solutions (when possible) * Learn constantly, educate others, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving
* 3+ years experience with SQL, Hive * 3+ years experience with Python, C++ * Experience managing large sets of data * Experience analyzing and producing reports from large sets of data * Knowledge with computer vision * Bachelors degree in Computer Science, Computer Vision, Engineering or similar * Communication experience and demonstrated experience working across disciplines to drive solutions
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