Position Summary: The Software Engineering Institute (SEI) is a federally funded research and development center located at Carnegie Mellon University. Our Advanced Mobile Systems (AMS) Initiative is seeking a Machine Learning Research Scientist. This is an excellent opportunity to work with leading researchers and faculty at a truly world-class institution. The Machine Learning Research Scientist will focus on advancing and applying machine learning technology to analyzing streaming data. The AMS team conducts applied research, matures and prototypes technology; and transitions technology to government organizations.
The ideal candidate will enjoy working with world-renowned researchers/engineers at the SEI, Carnegie Mellon University, and other universities and R&D centers. S/he will apply promising technologies to applications requiring rapid processing of large volumes of streaming data. The candidate should have a strong mathematics and/or computer science background and experience in machine learning technology and developing highly-distributed systems performing near-real-time analysis of data.
Minimum Qualifications and Requirements:
Education/Training: M.S. degree in computer science or related discipline with eight (8) years of experience or equivalent combination or training and experience. PhD strongly preferred.
Experience: Two or more (2+) years in three or more of the following: system/software architecture and development, virtual machine technology, distributed processing, data analytics, machine learning and/or natural language processing.
Skills/Abilities: Ability to contribute to machine learning research and design and develop advanced prototypes. Excellent analytical, problem solving and organizational skills. Ability to work successfully in small team environments, and communicate with prominent researchers and engineers. Interest in the application of advanced technologies to extremely complex and challenging problems
Mobility: Normally sedentary position with some mobility; i.e., able to travel to campus and potentially other locations.
Environmental Conditions: Usual office setting, close contact with CRT for long periods of time.
Mental: Ability to pay close attention to detail, meet deadlines, balance multiple tasks, work under pressure, and work with frequent interruptions.
Other: Candidates will be subject to a background check and must be eligible to obtain and maintain a Department of Defense security clearance.
Preferred Qualifications and Requirements:
Education/Training: PhD in Computer Science or related discipline with five (5) years of experience or equivalent combination of training and experience. Advanced coursework in machine learning/natural language processing. Advanced coursework in architecting highly-distributed systems. Additional course work in computer applications, software engineering and networking.
Experience: Four or more (4+) years’ experience in system/software architecture and development, virtual machine technology, distributed processing, data analytics, machine learning and/or natural language processing. Experience developing data analytics applications, and applications for intermittently connected, low bandwidth, and low power environments; sensor integration and fusion.
Skills/Abilities: Experience working with the intelligence community.
Accountability: Completes project tasks from routine to complex; is accountable for meeting established deadlines and project milestones with a commitment to decisions that have been made.
Direction: Expected to perform with limited supervision. Most normal duties and responsibilities are handled independently with the use of established research and engineering protocols and departmental and university procedures and policies.
Decisions: Works with researchers and developers to implement pragmatic solutions to complex problems.
Supervisory Responsibilities: Potential small team supervision.
Job Functions or Responsibilities:
30% Works with CMU, SEI, other researchers, and the intelligence community to enhance the state of the art in technologies to assist in the analysis of large volume and streaming data.
30% Works with CMU and SEI engineers to apply state of the art technologies to prototype systems that assist in the analysis of large volume and streaming data.
20% Attends meetings, submits work progress reports, and performs related duties as required.
20% Represents work plans and prototypes via publications, conferences, and meetings to the academic research, engineering, DoD, and first responder communities.
100% Total Effort
Organizational Chart : SSD Director > CSC Directorate Lead > AMS Initiative Lead > Machine Learning Research Scientist.
Carnegie Mellon University is an EEO/Affirmative Action Employer – M/F/Disability/Veteran.
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