Nishant Singh

AI Researcher

Bengaluru, Karnataka, India6 yrs experience

AI EnabledAI ML Practitioner

Key Highlights

Led a team impacting over 250 clients globally.
Developed a PII redaction system with 97.5% accuracy.
Built centralized GenAI services for 100k+ daily users.

Stackforce AI infers this person is a SaaS Data Science expert with a focus on Generative AI and Computer Vision.

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Skills

Core Skills

Data ScienceGenerative AiAi AgentsMlopsComputer Vision

Other Skills

AI Software DevelopmentAWSAWS SageMakerAmazon Web Services (AWS)Artificial Intelligence (AI)Basic Programming in CChatbotsData ModelingDeep LearningGoogle Agent Development kitKerasLarge Language Model Operations (LLMOps)Large Language Models (LLM)LeadershipMachine Learning Algorithms

About

As Lead Data Scientist at VMock, I oversee the Resume Parser, JD Parser, and Optimiser team while mentoring junior data scientists. My current focus includes building centralized GenAI services for resume parsing, grammar correction, and interview feedback, which serve over 100k daily users. Additionally, I’ve developed tailored GenAI-powered solutions for 250+ universities and organizations, along with an in-house PII redaction system achieving 97.5+% accuracy. My educational background in Aerospace Engineering from Dayananda Sagar Institutions has equipped me with a strong analytical foundation. Passionate about leveraging skills in GenAI, LLMOps, and AI Agents, I aim to deliver impactful solutions that enhance user experience and ensure data privacy.

Experience

6 yrs

Total Experience

1 yr 6 mos

Average Tenure

1 yr 10 mos

Current Experience

Vmock

Lead Data Scientist

Aug 2024 – Present · 1 yr 10 mos · Gurugram, Haryana, India · On-site

Led Resume Parser, JD Parser, Optimizer, Cover Letter and LinkedIn Aspire products mentoring junior data scientists across multiple projects, impacting 250+ clients globally
Architected a modular, section-aware GenAI resume parser that splits resumes into sections and routes them to specialized extractors; parallelized execution and streaming to reduce end-to-end latency and timeouts while boosting entity-level accuracy by 15%.
Built a centralized GenAI service for resume parsing, grammar correction, and interview feedback using Langchain, with a daily traffic of around 100k+
Delivered a multilingual GenAI backend supporting 5+ languages like english,spanish,french,german etc. across resume/JD parsing, optimization, cover letters, and LinkedIn features via a generalized LLM pipeline with auto language detection and per-locale prompt packs/taxonomies for high-accuracy, locale-aware outputs.
Developed tailored solutions for 250+ universities and staffing organizations, including resume and cover letter generation with GenAI Capabilities
Engineered an in-house PII redaction system to sanitize sensitive data and ensure client privacy with 97.5+% accuracy across entities' names, address, phone number, etc.
Created an AI agent framework applying the Google ADK to simulate a career coach chatbot, guiding candidates to increase user engagement
Orchestrated GenAI services on AWS ECS with distinct sync API and async worker fleets behind ALB, using SQS for job queues and S3 for payload staging; implemented auto-scaling via target tracking (CPU/memory), step scaling on custom CloudWatch metrics and scheduled scaling for predictable peaks.

MLOpsTeam LeadershipAI AgentsData ScienceVector DatabasesPrompt Engineering+10

Shadowfax

2 roles

Associate Lead Data Scientist

Jul 2023 – Aug 2024 · 1 yr 1 mo · Bengaluru, Karnataka, India

AWS SageMakerMLOpsTeam LeadershipComputer VisionData ScienceVector Databases+9

Senior Data Scientist II

Jul 2022 – Jun 2023 · 11 mos · Bengaluru, Karnataka, India

Building solutions based on Computer Vision for Fraud Detection Engine mainly categorised as:
Face Verification : Using Siamese Network to build a Rich Face Feature Extractor from our Riders Data and using those embeddings and various similarity based algorithms to detect any fraud while they login on our platforms
Document OCR Extraction: Building an OCR pipeline in order to extract various entities from goverment records like PAN card , Adhar cards and etc with an accuracy of approximately 98%
Rain Video Classification : Based on videos provided by riders, build a model to detect if there is rain occurring in clusters in order to generate tickets for activating rain surge charges with minimum tat, for riders statisfaction
Building and Maintaining Geocoding Engines based of Bert-Regression Models using Point-of-Delivery data from E-commerce Riders
Build an Automate Entity Recognition Engine from Addresses provided by our customers based on our past history to recognise patterns in addresses in order to solve problems like Pincode Updates, RTO , Route Optimization and etc.

AWS SageMakerMLOpsComputer VisionData ScienceVector DatabasesPyTorch+4

Quantiphi

Machine Learning Engineer | Computer Vision

Apr 2021 – Jul 2022 · 1 yr 3 mos · Bangalore Urban, Karnataka, India

Working on advance Computer Vision problems involving algorithms based on Image Segmentation, Object Detection, Action Recognition, Pose Estimation , Object Tracking etc.
Optimizing the Inferencing pipeline using Tensor-rt and ONNX models for better inference speeds
Creation of Docker Images of Machine Learning Models for Running Training jobs through AWS Sagemaker and Hyperparameter tuning for Sagemaker exposed hyper-parameters
Creation of Labelling jobs for Objection Detection , Object Tracking , Polygons , keypoints etc. through AWS
Image Data preprocessing and Creation of pipelines connecting different Models

AWS SageMakerMLOpsComputer VisionData SciencePyTorchPredictive Modeling+3

Decision point analytics

Data Scientist

Mar 2021 – Apr 2021 · 1 mo · Gurugram, Haryana, India

Worked on Time Series – Sales and Demand Forecasting for various CPG and FMCG Clients
Creating Price Elasticity for Share Gain opportunities

Data SciencePyTorchPredictive ModelingPattern RecognitionData Modeling

Self employed

Analyst Data Science

Feb 2019 – Mar 2021 · 2 yrs 1 mo · Greater Kolkata Area

NLP: Machine Translation Modeling with Encoder-Decoder Architecture
along with Loung's Attention developed from Scratch
Document Classification using Convolution Neural Network
Image Processing: Image Segmentation of Indian Roads Traffic using
UNET and CaNET Architecture
Forecasting: Univariate and Multivariate Forecasting using Statsmodel like AR, MA, ARIMA
ARMA, VR, and Deep Learning-based model through LSTM
Machine Learning: a.) Link Prediction Project - Based on Directed Graph and Feature Engineering
b.) Cancer Prediction - Based on NLP and Machine Learning Algorithms
d.) Question Pair Similarity - Feature Engineering

Data Modeling