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Hi, I'm Suraj Chandra, an AI/ML Engineer with over four years of experience shipping production-grade machine learning systems. I design end-to-end pipelines—from data ingestion and feature engineering to model training and API-based deployment—while keeping experiments reproducible and metrics trustworthy. I enjoy collaborating with product and data teams to translate fuzzy requirements into measurable KPIs, build NLP/GenAI capabilities when appropriate, and monitor models in production for drift and reliability. I value clear documentation and clean interfaces that enable reliable, scalable deployment.…Hi, I'm Suraj Chandra, an AI/ML Engineer with over four years of experience shipping production-grade machine learning systems. I design end-to-end pipelines—from data ingestion and feature engineering to model training and API-based deployment—while keeping experiments reproducible and metrics trustworthy. I enjoy collaborating with product and data teams to translate fuzzy requirements into measurable KPIs, build NLP/GenAI capabilities when appropriate, and monitor models in production for drift and reliability. I value clear documentation and clean interfaces that enable reliable, scalable deployment.

Suraj Chandra

AI Engineer, Data Scientist, AI Developer, +2

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Hi, I'm Suraj Chandra, an AI/ML Engineer with over four years of experience shipping production-grade machine learning systems. I design end-to-end pipelines—from data ingestion and feature engineering to model training and API-based deployment—while keeping experiments reproducible and metrics trustworthy. I enjoy collaborating with product and data teams to translate fuzzy requirements into measurable KPIs, build NLP/GenAI capabilities when appropriate, and monitor models in production for drift and reliability. I value clear documentation and clean interfaces that enable reliable, scalable deployment.…Hi, I'm Suraj Chandra, an AI/ML Engineer with over four years of experience shipping production-grade machine learning systems. I design end-to-end pipelines—from data ingestion and feature engineering to model training and API-based deployment—while keeping experiments reproducible and metrics trustworthy. I enjoy collaborating with product and data teams to translate fuzzy requirements into measurable KPIs, build NLP/GenAI capabilities when appropriate, and monitor models in production for drift and reliability. I value clear documentation and clean interfaces that enable reliable, scalable deployment.

Available to hire

Hi, I’m Suraj Chandra, an AI/ML Engineer with over four years of experience shipping production-grade machine learning systems. I design end-to-end pipelines—from data ingestion and feature engineering to model training and API-based deployment—while keeping experiments reproducible and metrics trustworthy.

I enjoy collaborating with product and data teams to translate fuzzy requirements into measurable KPIs, build NLP/GenAI capabilities when appropriate, and monitor models in production for drift and reliability. I value clear documentation and clean interfaces that enable reliable, scalable deployment.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

AI/ML Engineer at CORtracker

January 1, 2024 - Present

I built end-to-end ML pipelines from raw ingestion to deployment, enforcing reproducibility with versioned datasets, configs, and tracked experiments. I designed feature engineering workflows and leakage checks, improving offline metrics stability and making cross-validation results trustworthy across releases. I trained and tuned tree-based models (XGBoost/LightGBM) and developed deep learning prototypes in PyTorch/TensorFlow. I implemented NLP embedding flows and RAG foundations, wired vector search into inference paths for higher recall and faster retrieval. I exposed models through FastAPI REST services with Docker for batch and real-time inference. I added monitoring for model metrics and data drift signals, established MLOps with MLflow/W&B tracking and a model registry, and collaborated with stakeholders to define KPIs and acceptance tests.

Machine Learning Engineer at Capri Global

January 1, 2020 - July 1, 2022

Built supervised ML solutions using scikit-learn pipelines with standardized preprocessing, encoding, and evaluation for repeatable training runs. Performed EDA and statistical checks to validate assumptions, catching target leakage and data drift risks early. Developed robust feature sets from transactional and behavioral data, improving model separability. Tuned models with cross-validation and metric-driven selection, aligning deployment with business costs. Delivered model inference via Flask/FastAPI endpoints, documented contracts, and integrated with application teams. Automated training and scoring workflows with ETL fundamentals, reducing manual reruns and missed refresh windows. Implemented unit tests and validation gates for data and features, preventing silent failures. Worked with business teams to translate goals into measurable outcomes, and supported initial cloud deployments with IAM basics for predictable runtime spend.