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Machine Learning Engineer, PhD
I am looking for challenging and rewarding opportunities in machine learning applications or machine learning hardware/software co-design. Having completed a Ph.D. and postdoc in particle physics with the ATLAS experiment during the startup of the LHC and the discovery of the Higgs boson, I have 15+ years experience in data science, including techniques in data reduction, visualization, classification, statistical inference, and machine learning. Later, I was a machine learning engineer at Cerebras Systems, working with models for computer vision, machine translation, and large-scale language modeling. Read more at my website: https://rreece.github.io/
University of Pennsylvania
Doctor of Philosophy (Ph.D.), Experimental Particle Physics
January 1, 2006 – January 1, 2013
The University of Texas at Austin
Bachelor of Science (BS), Physics
January 1, 2003 – January 1, 2006
Tenstorrent
Senior Staff Machine Learning Engineer
October 1, 2024 – Present
Santa Clara, California, United States
Tenstorrent
Staff Machine Learning Engineer
October 1, 2022 – October 1, 2024
Santa Clara, California, United States
Cerebras Systems
Machine Learning Engineer
April 1, 2018 – August 1, 2022
Sunnyvale, California, United States
Insight Data Science
Artificial Intelligence Fellow
January 1, 2018 – March 1, 2018
Palo Alto, CA
University of California, Santa Cruz
Postdoctoral Fellow
July 1, 2013 – August 1, 2017
CERN
Researcher
June 1, 2006 – August 1, 2017
Geneva, Geneva, Switzerland
Cultural Fit Analysis
The candidate's career path is heavily focused on Machine Learning and scientific research. While this demonstrates strong analytical capabilities, the direct alignment with a 'Backend Engineer' role, which typically involves broader system design, API development, and database management, is not immediately apparent. The lack of explicit backend engineering projects or experience outside of ML/AI could indicate a potential gap in cultural fit for a traditional backend team.
Soft Skills & Operational Fit
The candidate's background in research and startup environments suggests adaptability, problem-solving, and a drive for innovation. However, specific soft skills and operational fit for a Backend Engineer role cannot be fully assessed without direct behavioral data.