Machine Learning Engineer · GenAI / LLM Engineer Bengaluru, India
Brejesh Balakrishnan.
Building reliable ML & GenAI systems — from data to deployment.
Machine Learning Engineer
- 1.5+ years of production engineering at Accenture — AWS-hosted REST APIs, >90% automated test coverage, high-latency responses cut from ~80% to <20%
- Ship LLM / RAG applications: agentic LangGraph pipelines, dense retrieval (Pinecone, FAISS), retrieval evaluation (recall@k, MRR, nDCG) and faithfulness / grounding checks
- Full MLOps in production — MLflow champion/challenger registries, Evidently drift monitoring, CI model-quality gates, Docker — with systems deployed live
Actively interviewing: ML / GenAI Engineer (Bengaluru · Remote) — available immediately
01Selected work
Projects built to ship, not to demo.
End-to-end ML and data systems — trained, evaluated, deployed, and documented.
RAG Agent Workbench
Agentic RAG backend: 8-node LangGraph pipeline with corrective retrieval, faithfulness verification, and SSE streaming.
Python · FastAPI · LangGraph · Pinecone · Groq · Tavily · Prometheus · Docker · Hugging Face Spaces · Streamlit
May 2026
Dog Breed Classification
Deep learning pipeline for 120-breed classification with transfer learning.
Python · TensorFlow · Jupyter
Nov 2025
Heart Disease Risk Predictor
Predictive model for cardiac disease classification from medical data.
Python · Scikit-learn · Pandas · Numpy
Oct 2025
Heavy Equipment Price Prediction
Regression model for predicting equipment resale values.
Python · XGBoost · Scikit-learn · Pandas
Sep 2025
02Experience
Production engineering first.
The reliability habits — testing, profiling, code review — come from shipping enterprise software, and they carry into every ML system I build.
Accenture
Jul 2024 – Mar 2026
Advanced Application Engineering Analyst
UnisLink
Jul 2023 – Aug 2023
Data Engineering Intern
Yaltech Global Consulting
Jul 2022 – Sep 2022
Machine Learning Intern
Youth India Foundation
Jan 2022 – Mar 2022
Sponsorship Intern
TREC-STEP
Apr 2021 – Jun 2021
Incubation & Proposals Intern
Story Points Delivered
Agile delivery on a financial-services platform at Accenture
High-Latency Responses Cut
AWS REST APIs fixed via profiling, SQL tuning, and caching
Automated Test Coverage
Unit, contract, and BDD tests tracked via SonarQube
03Stack
Tools chosen for the whole lifecycle.
From exploration to training to serving — and the engineering around it.
- Programming
Python
Java
JavaScript
TypeScript
HTML
CSS
- Data
- SQL
Pandas
NumPy
MySQL
MongoDB
Redis
- ML
scikit-learnXGBoostLightGBMCatBoostOptuna (HPO)SHAP (Explainability)
- Deep Learning
TensorFlow
PyTorch
- GenAI/NLP
Hugging FaceTransformers (NLP)RAG (Retrieval Augmented GenAI)LangChainLangGraphPineconeFAISSsentence-transformersLLM APIs (Groq · Gemini)Retrieval Evaluation (recall@k · MRR · nDCG)
- MLOps
- MLflowDVCDagsHubPandera (Data Contracts)Evidently (Drift Monitoring)
- DevOps
Docker
GitHub Actions
Jenkins
SonarQubePrometheus
- Frameworks
FastAPI
Flask
Streamlit
Spring Boot
React
Angular
- Cloud
AWS
AWS SageMakerAWS S3AWS LambdaAWS CloudWatch
- Tools
Git
GitHub
Jupyter
VS Code
Postman
Jira
Confluence
Slackpytest
- Visualization
Power BIMatplotlib
PlotlySeaborn
04Contact
Let's build something reliable.
Open to Machine Learning / GenAI roles — available immediately