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ML Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Loco
ML Engineer
June 12, 2026 – Present
video-summarization
July 29, 2021 – July 29, 2021
video-summarization — GitHub repository
View ProjectRecomendation-system-
May 19, 2020 – May 19, 2020
Recomendation-system- — GitHub repository
View ProjectHomomorpic-Hashing-
March 28, 2020 – March 29, 2020
Homomorpic-Hashing- — GitHub repository
View ProjectCardinality-Estimation
March 27, 2020 – March 27, 2020
Cardinality-Estimation — GitHub repository
View ProjectUniversity-of-Liverpool---Ion-Switching
March 22, 2020 – March 22, 2020
University-of-Liverpool---Ion-Switching — GitHub repository
View ProjectKaggle_Bengali.AI-Handwritten-Grapheme-Classification
February 20, 2020 – February 22, 2020
Kaggle_Bengali.AI-Handwritten-Grapheme-Classification — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong focus on individual, personal projects, primarily in Python and ML. While this demonstrates initiative, there is limited evidence of collaborative work, diverse team environments, or broader system integration skills beyond core ML algorithms. The single professional experience is current, making it difficult to assess adaptability or long-term commitment. The projects are mostly academic or competition-based, which might indicate a strong theoretical foundation but less exposure to production-grade ML system development and deployment challenges.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's experience is limited to a single current role, and no psychometric or English test results are available.