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Research Staff Member-Distributed AI

  • Country:US
  • State:NY
  • City:YORKTOWN HEIGHTS
  • Category:Research
  • Required Education:Doctorate Degree
  • Position Type:Early Professional
  • Employment Type:Full-Time
  • Contract Type:Regular
  • Req ID:135793BR
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Job Description
The Distributed AI team at IBM's T. J. Watson Research Center is seeking Researchers to develop the key concepts in distributed analytics, that is at the intersection of AI (Artificial Intelligence) and distributed computing technologies. This includes such areas of machine learning, Internet-of-Things (IoT), edge computing, distributed systems and algorithms, etc.

A proven scientific track record with publication in top-tier conferences and/or peer reviewed journals is required. The work is cross-disciplinary, and will require explorations in areas spanning machine learning, edge and distributed computing, computer networks, cloud computing, and IoT systems and data analytics. Candidates with experience and expertise in deep learning, multi-modal time-series data analysis, statistical modeling and analysis, and large-scale distributed systems are preferred.

A Research Staff Member (RSM) generates highly novel ideas (theoretical or experimental) in a specific engineering or scientific discipline and/or invents/designs complex products and/or processes. Such individuals may be involved in engineering these ideas to an advanced state of feasibility by evaluating alternatives and plans and participating in their implementation. The full-cycle of innovation to delivery is typically a multiple-year effort. RSMs disseminate, internally and externally, the results of such activities through publications, patent disclosures, seminar participation, internal documentation, etc. Externally, RSMs represent IBM at professional meetings, in professional societies and in university collaborations. Within IBM, RSMs function as internal consultants in the areas of their professional expertise. They may direct technically, and/or manage, within the broad mission of the group, activities of other research staff members and technical support persons.

A Ph.D. in computer science or a related field, in such disciplines as artificial intelligence, IoT systems and data analytics, and distributed computing and algorithms is required.











The World is Our Laboratory: No matter where discovery takes place, IBM researchers push the boundaries of science, technology and business to make the world work better. IBM Research is a global community of forward-thinkers working towards a common goal: progress.

Required Technical and Professional Expertise

  • Experience and expertise in creating and leveraging machine learning techniques to solve data analytics problems-3+ years
  • Expertise and experience in programming in one or more of these languages: Java, Python, C, C++, etc.-5+ years
  • Experience in effectively communicating research ideas and outcomes in technical communities through publications and presentations-3+ years



    Preferred Tech and Prof Experience

    • Advanced knowledge and expertise in developing and applying machine learning and AI techniques to solve real-world problems
    • Experience in utilizing IoT devices and analyzing multi-modal sensory data for help understanding physical environments and behaviors
    • Advanced knowledge in probabilities and statistical modeling and analysis
    • Proven track records of research through publications in top-tier conferences and peer-reviewed journals in areas relevant to AI, IoT, distributed systems, edge computing, etc.



    EO Statement
    IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

    Preferred Education: None Commissionable: No
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