machine learning engineer

Armeta builds an engineering intelligence layer for the construction and industrial sectors, transforming complex technical archives into accessible, actionable information. The company analyzes initial permitting and design-and-estimate documentation to ensure compliance with building codes, automating manual review workflows. The platform unifies and contextualizes critical engineering data, offering deployment options in cloud environments or on-premise.

• Design, develop, and deploy backend services and ML systems for document understanding and compliance products;
• Build backend ML services using FastAPI;
• Integrate LLMs, NLP, and computer vision models into applications and internal tools;
• Train and fine-tune models for NLP and computer vision tasks;
• Manage retrieval-augmented generation (RAG) workflows, including loading, processing, indexing, and searching data across vector and full-text stores;
• Work with SQL and NoSQL databases;
• Build end-to-end pipelines from data ingestion through model inference to production serving;
• Test, debug, and optimize AI/ML features to ensure accuracy, robustness, and scalability.

• 1–3 Years of experience in ML across NLP, computer vision, or deep learning;
• Hands-on experience designing and developing microservices with FastAPI;
• Production experience with vector databases or full-text search engines like Qdrant, Milvus, or Elasticsearch;
• Experience with LLM frameworks such as LangGraph, Haystack, or LlamaIndex;
• Experience working with multimodal LLMs and open-source models;
• Proficiency in Python and familiarity with ML frameworks like PyTorch, TensorFlow, or scikit-learn;
• Ability to work on-site in Astana and collaborate with cross-functional teams;
• Nice to have: Familiarity with construction, engineering, or industrial domains, document processing, or information retrieval systems.

• Office role in Astana, Kazakhstan.