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AI Engineer with 2+ years in LLMs, Machine Learning, and Data Science
AI Engineer with 2.5 years of experience in large language models (LLMs) and machine learning. Hands-on experience in building LLM solutions, including conversational agents, RAG systems, and LLM-powered chatbots using frameworks such as LangChain and LangGraph. Experienced in developing, training, evaluating, and deploying machine learning and deep learning models, from data preprocessing and feature engineering to scalable inference services in production environments at large scale. Proficient in Python, scikit-learn, PyTorch, TensorFlow, FastAPI, and Java Spring Boot, enabling seamless integration of ML workflows into reliable backend systems and RESTful APIs. Previously worked as a Business Data Analyst, translating complex data into actionable insights and supporting data-driven decision-making to improve business performance.
Kharazmi University
B.Sc · Industrial Engineering
August 1, 2017 – June 30, 2021
TOSAN (Banking and Payment Solutions Provider)
AI Engineer
July 1, 2024 – Present
India
Financial and Economic Group at Saman Bank
Data Scientist
November 1, 2023 – May 1, 2024
India
Sepinud Shargh
Business Data Analyst
March 1, 2021 – July 1, 2022
India
Cultural Fit Analysis
The candidate's experience spans banking and payment solutions, and financial groups, indicating adaptability to different industry contexts. The diverse technical skills (LLMs, ML, DL, time series, backend development) suggest a broad interest and ability to learn, which is positive for cultural fit in dynamic tech environments. However, the project diversity is somewhat limited to financial applications, and the overall experience duration is relatively short for a senior role, which might impact cultural fit in highly experienced teams.
Soft Skills & Operational Fit
The candidate lists strong analytical and problem-solving abilities, critical thinking, communication & teamwork, and the ability to manage multiple tasks under tight deadlines. These soft skills are crucial for a senior AI Engineer role, especially when dealing with complex problem domains and collaborative development environments. The experience in refactoring Python codebases also suggests an operational fit for maintaining high code quality.