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ML Engineer

Summary

Build and fine-tune NLP/LLM models for client projects, crafting pipelines and deploying production-ready AI features using PyTorch, LangChain, and vector databases.

ML Engineer (NLP / LLM)

We are looking for an ML Engineer with solid hands-on experience in Natural Language Processing, Large Language Models, and fine-tuning models on client-specific data.

This role is ideal for someone who enjoys solving real business challenges with modern AI tools and can turn raw client data into production-ready intelligent solutions.

You will join a project focused on building custom AI features powered by LLMs, including data preparation, model adaptation, pipeline development, and deployment support.

Requirements:

  • Practical experience with LLM fine-tuning and prompt engineering

  • Strong knowledge of PyTorch and/or TensorFlow

  • Experience with LangChain and NLP pipeline composition

  • Good understanding of text preprocessing, normalization, and dataset preparation

  • Experience deploying ML/NLP models in production environments

  • Knowledge of vector databases, embeddings, retrieval pipelines, and inference optimization

  • Ability to work independently and propose implementation approaches based on project goals

Responsibility:

  • Fine-tune and adapt LLMs such as GPT, LLaMA, and similar models for domain-specific use cases

  • Prepare, clean, normalize, and structure raw text data provided by clients

  • Build scalable NLP pipelines for training, inference, and integration into real products

  • Work with tools and frameworks such as PyTorch, TensorFlow, Transformers, Hugging Face, and LangChain

  • Select and integrate appropriate tools for embeddings, vector search, model serving, and inference optimization

  • Collaborate with developers, product teams, and stakeholders to deliver AI-driven features aligned with business needs

Cooperation format:

  • Project-based engagement

  • Opportunity to work on cutting-edge AI solutions for real client cases

  • Close collaboration with an experienced delivery team

  • Flexible setup depending on project scope and availability

See also

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