Saurabh Vaidya
Backend 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 @ Amazon
I’m an Applied Scientist with over seven years of experience leveraging Machine Learning and AI to solve complex business problems. Currently, at Amazon Business, I focus on developing ML-driven solutions for customer acquisition and identification, creating impactful strategies to drive growth. Previously, at Supportiv, I led initiatives in mental health innovation, improving recommendation systems by 20% and pioneering efficient NLP solutions that significantly reduced costs and execution time. At Amazon Alexa Privacy, I developed advanced privacy transformation techniques, safeguarding sensitive data while maintaining high model performance. Earlier at JPMorgan Chase, I utilized AI to streamline operational processes, saving resources and improving efficiency. My expertise spans deep learning, recommendation systems, NLP, and data privacy, with a proven track record of delivering measurable results across diverse industries. I’m passionate about building scalable AI systems that bridge innovation with real-world business impact. Let’s connect to explore how we can tackle challenging problems with cutting-edge technology.
Northeastern University
Master of Science - MS, Computer Science
January 1, 2018 – January 1, 2020
Dwarkadas J. Sanghvi College of Engineering
Bachelor of Engineering (B.E.), Computer Science
January 1, 2012 – January 1, 2016
Amazon
Applied Scientist II
January 1, 2025 – Present
Seattle, Washington, United States · On-site
Supportiv
AI / Machine Learning Engineer
January 1, 2023 – December 1, 2024
Amazon
Applied Scientist
February 1, 2021 – January 1, 2023
Seattle, Washington, United States
JPMorgan Chase & Co.
Machine Learning Engineer
July 1, 2016 – June 1, 2018
Mumbai, Maharashtra, India
Search Engine - Information Retrieval
November 1, 2018 – December 1, 2018
•Developed a search engine with components such as index creation, text transformation, retrieval models and evaluation metrics. • Used Pseudo Relevance feedback for query enrichment and BM25, tf-idf, JM smoothing and Lucene retrieval models. • Built snippet generation using Luhn’s algorithm for sentence significance factor calculation.
Avoiding food wastage
June 1, 2018 – Present
A Django based web platform that plans to serve as a way to avoid wasting food in households and restaurants/ events. It provides a portal for people to make a food donation and a portal for non-profits and other social welfare organizations to view the live donations and accept.
Football Match Winner Prediction
December 1, 2015 – April 1, 2016
• Developed a software to predict the outcome of a match using machine learning. It uses statistical data collected by crawling web pages from a match like shots,form,goals etc. to train the classifiers like Logistic Regression, Random forest and Naive Bayes to predict the outcome. • Tools- Python,Java,PyCharm (IDE).
MEDICAL STORE OPERATIONS SOFTWARE
October 1, 2014 – Present
• Developed a daily business operations software providing inventory management, invoicing, cart, medicine details as well as alternate medicines . User Friendly UI for customer profiles, employee profiles and sales statistics. • Tools used- Java, Sqlite, Netbeans.
Cultural Fit Analysis
The candidate's project portfolio shows a mix of academic and personal projects, including social impact (avoiding food wastage) and core computer science (search engine). Their professional experience is heavily concentrated in AI/ML roles, which aligns with a research-oriented or advanced technical culture. However, the target role is 'Backend Engineer', which is a significant pivot from their primary experience in Applied Scientist/ML Engineer roles. While they have some foundational Java/Python experience from projects, the depth in core backend engineering principles (e.g., distributed systems, API design, database optimization beyond basic SQL, cloud infrastructure) is not explicitly demonstrated, which could be a cultural fit challenge for a pure backend role.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight problem-solving, innovation (pioneered privacy data auditor), and efficiency improvements (reduced expenses, execution time). These indicate a strong operational fit for roles requiring initiative and impact. However, direct assessment of soft skills like teamwork or stress handling is not possible without psychometric test results or interview data.