Aniq.

About Aniq.

AI Engineer & Data Scientist | ML & Generative AI SpecialistI am an AI Engineer and Data Scientist focused on transforming raw data into reliable, production-grade intelligent systems. With nearly two years of hands-on experience, I work at the convergence of traditional Machine Learning and modern Generative AI, building solutions that are not just accurate—but scalable, maintainable, and business-driven. Core ExpertiseEnd-to-End AI EngineeringI design complete AI systems—from data ingestion and SQL-based pipeline construction to model deployment and API integration. My approach prioritizes robustness, reproducibility, and performance.Generative AI & LLM SystemsI architect Retrieval-Augmented Generation (RAG) solutions using LangChain and Hugging Face. My focus is on minimizing hallucinations, strengthening knowledge grounding, and delivering enterprise-level response reliability.Machine Learning EngineeringI build and optimize ML models using Scikit-learn and productionize them with FastAPI, ensuring seamless integration into real-world applications with low latency and high scalability.Data Infrastructure & EngineeringStrong foundation in Python and SQL for constructing idempotent pipelines, handling complex relational data structures, and managing hierarchical systems such as inventory and workforce datasets. Professional Impact• Successfully transitioned AI systems from experimental notebooks into live production environments using FastAPI and Azure AI.• Improved LLM response quality through structured prompt engineering and intelligent knowledge integration.• Applied MLOps practices including experiment tracking, model versioning, and structured deployment workflows to ensure long-term system stability. Engineering PhilosophyEffective AI engineering requires more than model accuracy—it demands clarity, reliability, and business alignment. I prioritize clean architecture, disciplined experimentation, and transparent communication to convert complex AI logic into measurable value.I continue to deepen my expertise in RAG architectures, cloud-native AI deployment, and responsible AI engineering to stay aligned with industry evolution.Technical Stack & Domains:AI Engineering • Data Science • Generative AI • LLM Systems • RAG Architectures • LangChain • Python • SQL • FastAPI • Azure • MLOps • Scikit-learn • Data Pipelines

Experience

1. Artificial Intelligence Engineer

   Mercor

   Jan 2025 — Present · Mumbai, IN

Education

• Jawaharlal Nehru Technological University Hyderabad (JNTUH)

  B.tech, Computer Science