Niloy Gupta
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning/Artificial Intelligence
I am a machine learning engineer based in San Francisco, focused on research-driven solutions that translate into scalable product impact. My expertise lies in building end-to-end large-scale machine learning systems for biomedical question answering, consumer finance, healthcare, and marketing, resulting in measurable business outcomes. I have led initiatives spanning large-scale statistical modeling, distributed model training, low-latency model serving infrastructure, interpretability, and revenue optimization. My work bridges foundational ML research and real-world deployment at scale.
Carnegie Mellon University
Masters, School of Computer Science
N/A – Present
National Institute of Technology Karnataka
B.Tech, Computer Science & Engineering
N/A – Present
Adyen
Staff AI Research Engineer
December 1, 2025 – Present
San Francisco, California, United States · On-site
Attentive
Staff Machine Learning Engineer
August 1, 2024 – November 1, 2025
San Francisco, California, United States · On-site
Lambent Logic
Co-Founder, CTO
May 1, 2023 – August 1, 2024
San Francisco Bay Area · Hybrid
Affirm, Inc.
Tech Lead Manager, Computational Finance
July 1, 2020 – April 1, 2023
San Francisco Bay Area
Affirm, Inc.
Staff Software Engineer, Machine Learning
September 1, 2018 – July 1, 2020
San Francisco Bay Area
Yelp
Machine Learning Engineer
February 1, 2016 – August 1, 2018
San Francisco Bay Area
Goldman Sachs
Software Engineer
June 1, 2012 – June 1, 2014
Bangalore
Cultural Fit Analysis
The candidate has worked in diverse environments, from large corporations (Goldman Sachs, Yelp, Affirm) to a startup they co-founded (Lambent Logic). This breadth of experience suggests adaptability. Their roles consistently involve leading and building ML systems, indicating a strong alignment with innovation and impact-driven cultures. The entrepreneurial experience also points to a proactive and ownership-oriented mindset. However, the lack of specific project details makes it difficult to fully assess collaboration style or specific cultural contributions beyond leadership.
Soft Skills & Operational Fit
The candidate's experience as a Co-Founder/CTO and Tech Lead Manager suggests strong leadership, strategic thinking, and project management skills. Their involvement in securing funding and addressing revenue leakage indicates business acumen and problem-solving capabilities. The description of 'scaling machine learning systems and managing talent' at Affirm further supports operational fit for senior roles.