Raghav Bansal
I’m a Machine Learning Engineer with almost 4 years at Samsung, building production-grade Machine Learning systems across on-device, cloud, and generative AI pipelines. I’ve worked on multilingual Natural Language Processing (NLP) models, Deep Learning, Retrieval-Augmented Generation (RAG) systems, and deployed Large Language Models (LLMs) at scale using Triton Inference Server and AWS.
My strengths include on-device AI (TensorFlow Lite, model quantization, unsupervised clustering), contextual search (Word2Vec, BERT), and building robust ML APIs integrated with Android and web services.
I’m currently open to opportunities focused on LLMs, on-device intelligence, Deep Learning, or scalable Machine Learning infrastructure.
- Role
Software, FastAPI, Machine Learning Engineer
- Years of Experience
9.58 years
Skillsets
- fine-tuning
- MCP
- model quantization
- NLP
- Ollama
- Room
- S3
- SQS
- Triton Inference Server
- Bash
- LLMs
- Hugging Face
- Jenkins
- Linux
- NumPy
- pandas
- PostgreSQL
- PyTorch
- rag
- Scikit-learn
- Auto Scaling
- Python
- Java
- SQL
- AWS
- Docker
- Flask
- Kotlin
- MLOps
- TensorFlow
- Python
- ChromaDB
- EC2
- FAISS
- FastAPI
- Gerrit
- Git
- Jira
- LangChain
Professional Summary
9.58Years
- Feb, 2026 - Present 3 months
Lead Engineer
Samsung R&D Institute India - Bangalore - Jul, 2022 - Feb, 20263 yr 7 months
Software Engineer
Samsung R&D Institute India - Bangalore - Feb, 2022 - Jul, 2022 5 months
R&D Intern
Samsung R&D Institute India - Bangalore - Jul, 2021 - Aug, 2021 1 month
Data Science Intern
Sabudh Foundation - Jul, 2021 - Oct, 2021 3 months
Research Intern
Bharti Institute of Public Policy, ISB - Oct, 2021 - Jan, 2022 3 months
Data Analyst
The Ballot House UK (India) - Feb, 2021 - Oct, 2021 8 months
Data Science Trainee (COE)
Sabudh Foundation - Jul, 2020 - Aug, 20211 yr 1 month
Mentor
Mentors Without Borders - Feb, 2020 - Jul, 20222 yr 5 months
Student Convener
Computer Society of India, Student Chapter-GNDEC, Ludhiana - May, 2019 - Jan, 2020 8 months
Committee Member
Computer Society of India, Student Chapter-GNDEC, Ludhiana
Work History
9.58Years
Lead Engineer
Samsung R&D Institute India - BangaloreFeb, 2026 - Present 3 months
Software Engineer
Samsung R&D Institute India - BangaloreJul, 2022 - Feb, 20263 yr 7 months
Health Orchestrator | FastAPI, LangGraph, MCP, PostgreSQL, WebSockets, Android, LLMs: Architected a multi-agent orchestration layer handling requests via WebSockets, reducing response latency by 30% while eliminating agent collisions through deterministic sequencing. Engineered PostgreSQL-backed session memory to persist context across 20+ turn interactions, improving clinical instruction recall by 40% and ensuring rigid agent boundaries. Deployed MCP-governed guardrails with custom hallucination checks, blocking 100% of non-compliant tool calls and securing tool-chain execution for safety-critical queries. Samsung Personal Health Records (PHR) | Triton, EC2, SQS, S3, Auto Scaling, Docker, LLMs: Orchestrated a scalable LLM inference service on AWS EC2 via Triton Inference Server, utilizing custom AMIs and Auto Scaling groups to optimize compute costs by 20%. Engineered an asynchronous processing pipeline using SQS and S3, decoupling data ingestion to reduce end-to-end latency by 70% and increasing throughput by 3x. Samsung Internet Browser Semantic Search | Python, ML, RAG, NLP, TensorFlow, FastAPI, LLMs: Engineered a hybrid semantic-search and autocorrect system by ensembling BERT contextual embeddings with Word2Vec and Doc2Vec, achieving 97% Top-k accuracy on complex queries. Productionized a 94-language polyglot NLU model served via FastAPI and integrated with Android (Retrofit), optimizing inference for real-time multilingual support. Architected a RAG pipeline using dense vector embeddings and GPT for contextual query generation, improving intent resolution rates by 30% via semantic grounding. Smart Vibration and Ringtone Adjustment System | TensorFlow Lite, CNN, Android On-device ML: Engineered an ultra-compact 719 KB on-device CNN for surface classification (98.8% accuracy), optimizing inference to run within 610 KB RAM & 10 MB ROM to drive adaptive haptic feedback.
R&D Intern
Samsung R&D Institute India - BangaloreFeb, 2022 - Jul, 2022 5 months
Text Summarization Model Development | EncoderDecoder NLP, Python: Developed a text summarizer using EncoderDecoder NLP architecture with attention mechanism, achieving 97% accuracy.
Data Analyst
The Ballot House UK (India)Oct, 2021 - Jan, 2022 3 months
Research Intern
Bharti Institute of Public Policy, ISBJul, 2021 - Oct, 2021 3 months
Data Science Intern
Sabudh FoundationJul, 2021 - Aug, 2021 1 month
Data Science Trainee (COE)
Sabudh FoundationFeb, 2021 - Oct, 2021 8 months
Mentor
Mentors Without BordersJul, 2020 - Aug, 20211 yr 1 month
Helping underprivileged young people become passionate professionals
Student Convener
Computer Society of India, Student Chapter-GNDEC, LudhianaFeb, 2020 - Jul, 20222 yr 5 months
Committee Member
Computer Society of India, Student Chapter-GNDEC, LudhianaMay, 2019 - Jan, 2020 8 months
Major Projects
2Projects
Smart Vibration and Ringtone Adjustment System
Trained a CNN model on accelerometer data for real-time surface classification, achieving 98.8% accuracy and enabling automatic vibration/ringtone adjustment. Collected and processed sensor data, and optimized a TensorFlow model for on-device inference under 10MB ROM and 610KB RAM.
Samsung Cloud Emergency Backup
Developed an on-device ML based emergency backup with TensorFlow Lite and unsupervised clustering, reducing backup latency by 50%.
Education
Bachelor of Technology in Computer Science and Engineering
Guru Nanak Dev Engineering College (2022)