10/20/2026 updated
100 % available
AI/ML Engineer | High-Performance ML Pipelines & Real-Time Agents
Puducherry, India
Worldwide
M.Sc. StatisticsMachine Learning & Engineering
Expertise in Multi-Modal Concepts, Vector Embeddings, Feature Engineering, Classification & Regression Models, Statistical Analysis, Hyperparameter Tuning (RandomizedSearchCV), and Overfitting Resolution.
Architecture & Latency Optimization
Proficiency in Low-Latency Inference Optimization, System Instruction Tuning, Guardrails & Response Relevance Verification, and Custom Metrics Evaluation.
Data Engineering & Pipelines
Strong background in High-Dimensional Dataset Curation, Dataset Ingestion & Preprocessing (200k+ records), Multicollinearity Resolution, and Automated Data Extraction Pipelines.
Python (Advanced)
Advanced programming skills in Python for building scalable ML pipelines, data preprocessing, and deploying containerized services.
FastAPI & RESTful APIs
Experience integrating ML models into low-latency RESTful APIs using FastAPI for streamlined cloud performance.
Docker & Containerization
Deployment of containerized services via Docker to support scalable and efficient cloud infrastructure.
LangChain & Vector Databases
Application of LangChain and Vector Databases (FAISS, Chroma) for building end-to-end RAG systems and conversational AI pipelines.
Frameworks & Tools
Hands-on experience with Streamlit, Pandas, NumPy, SQL, R, Git, GitHub, Azure App Services, XGBoost, and Scikit-Learn for data science and ML workflows.
Expertise in Multi-Modal Concepts, Vector Embeddings, Feature Engineering, Classification & Regression Models, Statistical Analysis, Hyperparameter Tuning (RandomizedSearchCV), and Overfitting Resolution.
Architecture & Latency Optimization
Proficiency in Low-Latency Inference Optimization, System Instruction Tuning, Guardrails & Response Relevance Verification, and Custom Metrics Evaluation.
Data Engineering & Pipelines
Strong background in High-Dimensional Dataset Curation, Dataset Ingestion & Preprocessing (200k+ records), Multicollinearity Resolution, and Automated Data Extraction Pipelines.
Python (Advanced)
Advanced programming skills in Python for building scalable ML pipelines, data preprocessing, and deploying containerized services.
FastAPI & RESTful APIs
Experience integrating ML models into low-latency RESTful APIs using FastAPI for streamlined cloud performance.
Docker & Containerization
Deployment of containerized services via Docker to support scalable and efficient cloud infrastructure.
LangChain & Vector Databases
Application of LangChain and Vector Databases (FAISS, Chroma) for building end-to-end RAG systems and conversational AI pipelines.
Frameworks & Tools
Hands-on experience with Streamlit, Pandas, NumPy, SQL, R, Git, GitHub, Azure App Services, XGBoost, and Scikit-Learn for data science and ML workflows.
Languages
EnglishFluent
Project history
Deep coursework in production-level machine learning models, modern AI frameworks, and end-to-end data pipeline design.
Active member of SOTC (Free Software Hardware Movement); led collaborative open-source technology initiatives and code-base architectures.
Architected an end-to-end data ingestion and RAG system via vector embeddings to decrease text hallucinations. Optimized model prompt components and explicit system instructions to lower inference response latency. Enforced custom automated evaluation metrics and relevance guardrails to analyze data streams and catch ingestion errors. Technologies: Python, LangChain, Vector DB, Streamlit.