
Enes
From Turkey (UTC+3)
14 years of commercial experience
Lemon.io stats
4
projects done640
hours workedOpen
to new offersEnes – Machine learning, Python, NLP
Tarik Altuncu is a data engineer and machine learning expert with a PhD in Graph Theory. Proficient in Python, Pandas, and Scikit-learn, he has delivered high-impact NLP and AI solutions, including retrieval-augmented generation (RAG) systems. With strong ML concepts and problem-solving skills, he excels in AI-driven and data-intensive projects.
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Let’s get started today!Experience Highlights
AI Expert
Assistant AI chatbots for students in an online school for all grade levels.
- Created assistant AI chatbots for students in K12;
- led the AI team;
- used vector databases and RAG;
- used open-source LLMs and GPT API;
- worked on the API integration;
- was responsible for all the back-end work.
AI Developer
Dynamically select an LLM based on quality, cost and latency dimensions given a prompt and its extracted intent.
Created the model to select the best model for a given natural language query.
ML Lead / AI Expert
LinkedIn-like candidate recommendation engine for C-Level people (board members, CTO, CFO, etc.)
- Was executive for a search recommendation engine with LLMs;
- created job function and specialism prediction from candidate info, etc.;
- used open-source LLMs and GPT APIs;
- finetuned Mistral-7B and Mistral-8x7b in single and multi-GPU settings;
- used quantization methods such as GPTQ, AWQ.
Lead ML Engineer / AI Expert
Generative AI system to create advertisement text and images using LLMs and text2image models.
- Worked on OSS and API based LLM such as llama2 and OpenAI GPT APIs;
- fine-tuned and used several text2image models (SD versions, SD, XL, etc.);
- created APIs for all these using flask API;
- used chatbots in advertising to create advertisement text and paired them with text2image models to create banners.
Senior ML Engineer / AI Expert
Categorization and processing of Insurance documents with AI.
- Created several models for insurance doc type classification for different file formats and handwritten scanned docs;
- fine-tuned and used several OSS deep learning models such as pix2struct, donut and layoutllm to process the files;
- created APIs on top of these models;
- used chatbots for insurance documents understanding.
Data Scientist
Vehicle make-model-body type-color-year prediction ML model to make users' car ads creation process much easier.
- Worked on a Very Large-Scale NLP-Computer Vision Project to infer categories of ads (trained and tested with tens of millions of ads) and deployed successfully;
- worked on a Very Large-Scale Machine Learning (Deep Learning-Computer Vision) Project (Fine-grained vehicle classification: make, model, body type, color, year of a car). Designed, implemented, and deployed it end to end, including:
- Prototyped in Keras, implemented with Tensorflow with high training performance;
- Trained with more than 32+ millions of images on Google Cloud Compute Engine in multi-GPU setting, reaching state-of-the-art accuracy Deployed the model on Google ML Engine and exposed it on Compute Engine with Python Flask;
- Deployed the model on Tensorflow Serving on on-premise datacenter and implemented a Rest API with Flask for production use.