Data Research Engineer

Sight and Sound play a large role in our day-to-day experiences. We believe data can play a huge role in making the experiences personalized and resilient. Data is critical to synthesizing experiences that are otherwise unimaginable. We are interested in a variety of topics including big data management, self-service data cleaning and transformation at scale, data quality, search and discovery of structured data, information extraction, time-series and heterogenous data analytics, metadata management, applied AI, machine learning and data mining, data visualization, natural language processing and big data systems including systems' concerns such as: resource management, storage, caching, query processing, query optimization, security, and privacy. Investigate heterogenous data management techniques and polystore systems, including the application of AI & machine learning techniques to foundational data management problems including data quality, data profiling, data integration and schema matching. Develop tools and frameworks to enable scalable development of machine learning models and data science algorithms across heterogenous data domains, including tabular, time series, text, audio and video. Create distributed data processing architectures that leverage “compute at the edge” to enable novel use cases and applications such as predictive routing, data-driven experiences, and adaptive environments. Work with ATG researchers to understand data-related opportunities in peer researchers' domains such as applied AI and machine learning in Audio / Video domains. Technical depth: Necessary technical knowledge to create new SW architecture needed for real time just in time processing for audio/video algorithms running on distributed fashion between cloud and edge devices. Basic knowledge on Audio/Video streaming formats. Explore new technologies: Openness to learn new areas and innovate in the new areas. Then influence and collaborate with BG partners put the technology into production. Work with a sense of Urgency: Responds aggressively to changing trends and new technologies and creates new algorithms to capitalize on them. Takes appropriate risks to be ahead of the competition and the market. Collaborate: Collaborate with and influence peers in developing industry-leading technologies. Work with external trendsetters and technology drivers in academia and in partner enterprises. Expertise in data management, data cleaning, distributed systems, database storage engines, query processing and query optimization, and applied data science