Vaibhav Bhardwaj

AI/ML Engineer

Delhi, India 2+ yrs exp 84 · Excellent

About

AI/ML Engineer with 2 years of experience designing and deploying end-to-end AI and machine learning systems aligned with product requirements. Proficient in Generative AI, ML and MLOps — with hands-on expertise across the full ML lifecycle: data collection, preprocessing, feature engineering, model training and fine tuning (PEFT/LoRA), evaluation, and REST API deployment. Skilled in translating business requirements into data-driven solutions.

Skills & Expertise (38)

Python Advanced

8.0/10

Years Exp

Machine Learning Intermediate

7.5/10

Years Exp

TensorFlow Intermediate

7.5/10

Years Exp

PyTorch Intermediate

7.5/10

Years Exp

Gen AI Intermediate

7.5/10

Years Exp

Natural Language Processing Intermediate

7.5/10

Years Exp

Deep Learning Intermediate

7.5/10

Years Exp

Adaptability Intermediate

7.0/10

Years Exp

Team Collaboration Intermediate

7.0/10

Years Exp

Communication Intermediate

7.0/10

Years Exp

Critical thinking Intermediate

7.0/10

Years Exp

Model Deployment Intermediate

7.0/10

Years Exp

Exploratory data analysis Intermediate

7.0/10

Years Exp

Model Evaluation Intermediate

7.0/10

Years Exp

Feature Engineering Intermediate

7.0/10

Years Exp

Statistical Modeling Intermediate

7.0/10

Years Exp

Analytical Problem-Solving Intermediate

7.0/10

Years Exp

AWS Intermediate

7.0/10

Years Exp

SQL Intermediate

6.5/10

Years Exp

REST APIs Intermediate

6.5/10

Years Exp

Kubernetes Intermediate

6.5/10

Years Exp

Computer Vision Hugging Face RAG agentic AI Amazon S3 Amazon Sagemaker Prototyping MLflow Data Preprocessing SMOTE PCA Hypothesis Testing scikit-learn LangChain Vector Databases bash scripting C++

Work Experience

AI & ML Engineer (Associate)

NetEdge

Dec 2024 - Present

Architected an end-to-end RAG pipeline using semantic chunking, FAISS vector search, and sentence-transformer embeddings; deployed a Dockerized FastAPI backend with concurrent multi-patient querying validated under load testing. Reduced retrieval time from ~8 min to <10 sec (98% reduction), achieved >90% retrieval relevance across 500+ clinical notes, and cut pre-consultation prep time by ~60% — quantified and reported to stakeholders.

Machine Learning Intern

Unified

Oct 2024 - Dec 2024

Contributed to an end-to-end ML pipeline for insurance purchase prediction (AUC-ROC: 0.87); assisted in understanding business requirements and translating them into feature engineering and modeling strategies. Performed initial data familiarization, identified quality problems, and applied domain-driven statistical analysis (chi-square, ANOVA, VIF) — reducing feature count by 35% while maintaining predictive performance.