Senior Data Researcher

• 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 researchers to understand data-related opportunities in peer researchers’ domains such as applied AI and machine learning in Audio / Video domains.

What You Need To Succeed:

• 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.
• Invent & Innovate: Develop short and long-term technologies, algorithms and software tools that will help make Dolby a world leader in enhancing the sight and sound associated with digital content consumption. 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.

• PhD in Computer Science, or similar fields
• Background in relational databases, big data systems, and data analytic systems
• Expertise in data management, data cleaning, distributed systems, database storage engines, query processing and query optimization, and applied data science
• Knowledge of statistics and machine learning
• Proficiency in data structures and algorithms
• Familiar with git and project management tools, such as JIRA
• Excellent problem-solving and partnership skills
• Excellent communication and presentation skills
• Relevant publications in data mining / database conferences (e.g., SIGMOD, VLDB, ICDCS, IEEE BigData, ICDE, KDD, WSDM, ICDM, WEB)
• Bonus: Experience with Databricks / Spark in addition to using multiple Cloud services’ data products and services
• Bonus: Experience with AI models and cloud-based software development of AI models