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Aberdeen, Maryland, United States of America
JOB #R1900223

Deep Learning Researcher

Working at ICF

Working at ICF means applying a passion for meaningful work with intellectual rigor to help solve the leading issues of our day. Smart, compassionate, innovative, committed, ICF employees tackle unprecedented challenges to benefit people, businesses, and governments around the globe. We believe in collaboration, mutual respect, open communication, and opportunity for growth. If you’re seeking to make a difference in the world, visit www.icf.com/careers to find your next career. ICF—together for tomorrow.

ICF won a new research and development task order supporting a world class research laboratory in Maryland.  ICF will help the Army develop new artificial intelligence and machine learning algorithms to solve current and future problems facing the DoD.  About our work: From building the system that served as the model for network defense services within the U.S. Department of Defense to improving machine-to-machine learning for better cyber defense to patenting a new way to visualize cyber threats using virtual reality technology, we innovate to stay one step ahead. We are excited to hire a DOD cleared Deep Learning Researcher for Aberdeen, MD

In this role you will:  

  • Conduct R&D in deep learning, neural networks, and neuromorphic systems/processing.
  • Develop new algorithms and extend existing artificial intelligence and machine learning algorithms for application to Army-specific data
  • Research and develop decentralized and distributed computing algorithms to include application of distributed ledgers to coordinate devices and share information
  • Develop and exercise data sciences and statistical modeling approaches for distributed processing and analysis of large datasets

  Key Responsibilities: 

  • Kernel modifications for optimization of file I/O, power, and performance and verification and validation of updates along with performance assessments
  • Benchmarking efforts for computational kernels both within a node and as part of a parallel, heterogeneous processing paradigm
  • New novel and production hardware evaluations and integration within the ARL computing infrastructure
  • Development of new parallel programming methodologies and models in various formats to include SPMD (Single Program Multiple Data), MIMD (Multiple Instructions) and Multiple Data, and SIMD (Single Instruction Multiple Data) parallelism techniques.
  • Preparation of reports, papers, presentations, and other documentation to record and/or publish findings and results of research 

Basic Qualifications:

  • Candidate must be able to obtain, and maintain, the proper clearance required for this position 
  • PhD. preferred, but may consider a MS/BS degree in Computer Science, Computer Engineering, Mathematics, or Physics
  • Candidates shall have significant prior published experience in AI/ML frameworks, and work experience with ns-3 simulation and data visualization
  • Working knowledge of Python, C, C++, and distributed version control systems including Git.
  • Working knowledge of Distributed ledger development, smart contract development & blockchain development.
  • Proficient in Linux OS environment

ICF is an equal opportunity employer that values diversity at all levels. (EOE – Minorities/Females/ Protected Veterans Status/Disability Status/Sexual Orientation/Gender Identity)

Reasonable Accommodations are available for disabled veterans and applicants with disabilities in all phases of the application and employment process. To request an accommodation please email icfcareercenter@icf.com and we will be happy to assist. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. Read more about non-discrimination: EEO is the law and Pay Transparency Statement.

Maryland Client Office (MD88)

Who is ICF?

A consulting services company of over 5,000 experts across 67 countries, but not your typical consultants
LEARN MORE ABOUT ICF

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