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Enes – Machine learning, Python, NLP, experts in Lemon.io

Enes

From Turkey (GMT+3)

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Machine Learning EngineerSenior
Data ScientistSenior
Tech lead
AI EngineerSenior
Hire developer
13 years of commercial experience
Adtech
AI
Automotive
Edtech
Human resources
Insurance
AI software
Chatbots
Lemon.io stats
2
projects done
376
hours worked
Open
to new offers

Enes – Machine learning, Python, NLP

Enes is a highly experienced Senior Data Scientist and Machine Learning Engineer/Team lead with over 13 years of expertise. His focus includes natural language processing and computer vision, and he has a strong track record in projects involving generative AI, image creation, document classification, and large-scale ML models. Furthermore, Enes is well-versed in Docker, Kubeflow, GCP, Google Vertex AI, and APIs from Twitter and LinkedIn. He also excels in managing non-technical stakeholders and has experience in genomics and telecommunications. With strong communication skills and a Ph.D. in Computer Engineering, he will be a valuable asset for any team.

Main technologies
Machine learning
14 years
Python
14 years
NLP
14 years
AI
14 years
Additional skills
PyTorch
Tensorflow
Computer Vision
AWS
MongoDB
GCP
ETL
Flask
MLOps
SQL
Keras
Apache Hadoop
Deep Learning
Scikit-learn
GPT
LangChain
AWS SageMaker
Microsoft Azure
Docker
Kubernetes
Pandas
Selenium
Rewards and achievements
Tech interviewer
June 2024: Vlada Summary
Ready to start
1 week
Direct hire
Potentially possible

Experience Highlights

AI Developer
May 2023 - Feb 20248 months
Project Overview

dynamically select an LLM based on quality, cost and latency dimensions given a prompt and its extracted intent

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Responsibilities:

Created the model to select best model for a given natural language query

Project Tech stack:
PyTorch
Kubernetes
LLM
Python
ML Lead / AI Expert
Dec 2022 - Jan 20241 year 1 month
Project Overview

LinkedIn-like candidate recommendation engine for C-Level people (board members, CTO, CFO, etc.)

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Responsibilities:
  • 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.
Project Tech stack:
Machine learning
Deep Learning
AI
PyTorch
Computer Vision
Flask
NLP
MLOps
Scikit-learn
Lead ML Engineer / AI Expert
Nov 2021 - Jul 20231 year 8 months
Project Overview

Generative AI system to create advertisement text and images using LLMs and text2image models.

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Responsibilities:
  • 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.
Project Tech stack:
Python
SQL
PyTorch
Machine learning
NLP
Computer Vision
Deep Learning
Cloud Computing
AWS
Flask
AI
MLOps
Senior ML Engineer / AI Expert
May 2022 - May 20231 year
Project Overview

Categorization and processing of Insurance documents with AI.

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Responsibilities:
  • 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.
Project Tech stack:
Machine learning
NLP
PyTorch
Scikit-learn
Deep Learning
AI
Flask
SQL
AWS
Data Scientist
Sep 2017 - Jan 20202 years 4 months
Project Overview

Vehicle make-model-body type-color-year prediction ML model to make users' car ads creation process much easier.

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Responsibilities:
  • 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:
  1. Prototyped in Keras, implemented with Tensorflow with high training performance;
  2. 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;
  3. Deployed the model on Tensorflow Serving on on-premise datacenter and implemented a Rest API with Flask for production use.
Project Tech stack:
Python
Tensorflow
Keras
GCP
GCP Compute Engine
SQL
Apache Hadoop
Flask
Machine learning
Deep Learning
NLP
Computer Vision
Cloud Computing
MongoDB
MySQL
AI
MLOps

Education

2017
International Relations, Election Forecasting using Twitter data, ML and NLP
MA
2023
Computer Engineering
PhD

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