Enes
From Turkey (GMT+3)
14 years of commercial experience
Lemon.io stats
2
projects done376
hours workedOpen
to new offersEnes – 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
Additional skills
Rewards and achievements
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ASAPDirect hire
Potentially possibleExperience Highlights
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 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.