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