Job Summary: 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.
Key Responsibilities:
- 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.
Desired Background:
- 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