Majid Mirbagheri
ML EngineerAudio | Machine Learning | DSP
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Audio | Machine Learning | DSP
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I am an ML algorithm engineer leading projects on the cross section of machine learning and signal processing for audio capture and render applications. My core competencies span from building machine learning algorithms for various domains to serving as the "translation layer" between cross functional partners. I am passionate about applying my expertise in machine learning to new domains and bringing next-generation technologies to life.
University of Maryland
Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering
January 1, 2008 – January 1, 2014
University of Maryland
Master of Science (MS), Electrical and Computer Engineering
January 1, 2006 – January 1, 2008
Sharif University of Technology
Bachelor's Degree, Electrical Engineering
January 1, 2002 – January 1, 2006
Apple
Senior Machine Learning Algorithm Engineer
April 1, 2023 – Present
Los Angeles, California, United States
Starkey Hearing
Senior Machine Learning Algorithm Engineer
February 1, 2021 – April 1, 2023
Seattle, Washington, United States
University of Washington
Affiliate Assistant Professor
August 1, 2019 – March 1, 2023
Seattle, Washington, United States
Machine Learning Researcher
August 1, 2017 – August 1, 2019
Greater Seattle Area
University of Washington
Postdoctoral Research Fellow
October 1, 2014 – July 1, 2017
Seattle, WA
Audience, Inc.
Advanced Algorithm Design Intern
May 1, 2013 – November 1, 2013
San Francisco Bay Area
University of Maryland
Graduate Research Assistant
August 1, 2006 – June 1, 2014
College Park, MD
Cultural Fit Analysis
The candidate's diverse experience across industry (Apple, Facebook, Starkey Hearing) and academia (University of Washington, University of Maryland) demonstrates adaptability and a broad perspective. The focus on ML for audio applications aligns well with specialized ML roles. However, the lack of explicit project details or community involvement makes a comprehensive cultural fit assessment challenging. The target role of ML Engineer aligns well with the candidate's extensive experience in ML algorithm development and research.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in developing and deploying ML solutions and leading research efforts, suggesting strong problem-solving and project leadership skills. The academic background and research roles indicate a capacity for independent work and innovation. However, specific details on collaboration, stress handling, or work attitude are not available from the provided data.