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AI Engineer with experience in perception, autonomy, and LLMs
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Massachusetts Institute of Technology
Doctor of Philosophy - PhD, Nuclear Engineering
N/A – Present
Rensselaer Polytechnic Institute
Master's degree, Applied Mathematics
N/A – Present
Rensselaer Polytechnic Institute
Bachelor's degree, Mathematics
N/A – Present
Stack AV
Staff Software Engineer, Autonomy
April 1, 2025 – Present
Meta
Software Engineer, Machine Learning
January 1, 2023 – January 1, 2024
Xwing
Software Engineer, Perception
January 1, 2022 – January 1, 2023
Valo
Senior Staff Software Engineer
January 1, 2021 – January 1, 2022
Mythic
Senior Staff Software Engineer
January 1, 2019 – January 1, 2021
Deep Sentinel
Senior Machine Learning and Computer Vision Engineer
January 1, 2017 – January 1, 2019
NVIDIA
Senior Deep Learning and Computer Vision Software Engineer
January 1, 2016 – January 1, 2017
Twist Bioscience
Principal - Informatics
January 1, 2014 – January 1, 2016
Edgestream Partners
Research Staff
January 1, 2008 – January 1, 2014
Cultural Fit Analysis
The candidate's background in various innovative companies (Stack AV, Meta, Xwing, NVIDIA) suggests an adaptability to fast-paced, research-driven, and technically challenging environments. The diverse project experience aligns with a culture that values innovation and deep technical contributions. However, the lack of project details or specific team collaboration experiences makes a comprehensive cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate's extensive experience in diverse, high-tech environments suggests strong problem-solving, adaptability, and potentially leadership skills. The progression through senior roles indicates operational effectiveness and ability to handle complex projects. However, without psychometric test results or interview data, specific soft skills and operational fit cannot be fully assessed.