Abhishek Singh

M.Tech Data Science student with hands-on experience in GenAI, RAG pipelines, and MLOps on Azure. IEEE published researcher. Proven ability to build and deploy end-to-end ML systems achieving 94% accuracy at sub-200ms latency. Deep expertise in LLM orchestration (LangChain, FAISS), scalable ML pipelines (Docker, MLflow, CI/CD), and cloud deployment on Azure. Active researcher in agentic AI, LLM fine-tuning (LoRA/QLoRA), and multimodal RAG systems.

L2 Data Analysis at DCS (2023-08 – 2024-02)

Engineered time-series sensor data pipelines and developed predictive ML models for smart EV project

• Engineered time-series sensor data pipelines on the Thingworx IoT platform for a smart EV project, diagnosing performance bottlenecks across 10+ vehicle telemetry signals and delivering data-driven optimization recommendations that improved in F1 Score, reducing false-positive fault detection rate from ~42% to ~27%.
• Developed and optimized predictive ML models using Python, Scikit-learn, and TensorFlow achieving a 35% improvement in F1-score through systematic feature engineering, cross-validation, and hyperparameter tuning via GridSearchCV

Master of Technology in Data Science – Bennett University (2024 – present)

Bachelor of Technology in Computer Science – GLA University (2019 – 2023)