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I’m a Data Scientist / AI/ML Engineer based in Germany, focused on building production-grade AI systems that teams can trust: reproducible experiments, measurable quality, robust deployment, and clear monitoring.
Core strengths
- AI/ML Engineering: end-to-end pipelines, evaluation, deployment, monitoring
- LLM systems (RAG + Agents): retrieval quality, grounded responses, tool-using workflows, guardrails
- Multimodal CV: representation learning, practical pipelines for perception tasks
- MLOps / LLMOps: CI/CD, containers, infra as code, monitoring and iteration loops
- Evidence first: define success metrics, build evaluation harnesses, track regressions
- Systems mindset: latency/cost constraints, failure modes, observability, safe fallbacks
- Clean delivery: reproducible environments, tests, CI, documentation, simple interfaces
| Languages | Python-first • Strong engineering fundamentals | |
| ML / Data |
|
Modeling • experimentation • fast dataframes (Polars) |
| LLM / GenAI |
|
RAG • agents • embeddings • evaluation • tool calling |
| Backend / APIs | Fast APIs • integrations • production services | |
| Cloud / MLOps |
|
Deployments • CI/CD • IaC |
| Data / Infra | Storage • streaming • caching | |
| Apps |
|
Demos • internal tools • prototypes that ship |
| Observability / Dev | Monitoring • debugging • reliability |
| Project | What it is | Stack | Link |
|---|---|---|---|
| 🔎 RAG on Azure (FastAPI) | Practical RAG service design for grounded answers | FastAPI, Azure, Search/RAG | https://github.com/BharAI-Lab/rag_azure_fastapi |
| 🧠 RAG with NVIDIA NIM | Lightweight doc-chat app workflow | NIM, Python, RAG | https://github.com/SurajBhar/rag_nim |
| 📊 Tabular ML Prediction | Pipeline: prep → modeling → evaluation | Python, scikit-learn | https://github.com/SurajBhar/hrprediction |
| 🎬 Movie Sentiment Prediction | Text classification with clear preprocessing + eval | NLP, Python | https://github.com/SurajBhar/moviesentiment |
| 🧪 Bayesian Optimization | Practical experiments + optimization workflows | Python | https://github.com/SurajBhar/bayesian_opt |
| 🗄️ SQL Analytics Project | SQL + analytics case study | SQL, Python | https://github.com/SurajBhar/data_science_sql_project |
| 🎓 Academic (CV) | Master’s thesis & studies repositories | CV, Python | https://github.com/SurajBhar/masterarbeit_sb • https://github.com/SurajBhar/studienarbeit_repository |
- Tableau — Amazon Sales Analysis:
https://public.tableau.com/app/profile/suraj.bhardwaj2195/viz/Amz_Dashboard_22Sep/ItemAnalysis
