Machine Learning Engineer

📌 ACTUAL LOCATION: ASTANA, KAZAKHSTAN (ON-SITE)

Company Description

Armeta builds an engineering intelligence layer for the construction and industrial sectors, turning complex technical archives into accessible, actionable information. In Kazakhstan, Armeta analyzes initial permitting documents (ИРД) and design-and-estimate documentation (ПСД) to check them for compliance with building codes and regulations, automating review workflows that have historically been fully manual. The platform unifies, contextualizes, and makes queryable critical engineering and construction documents, and is deployed in customers' cloud environments or on-premise for flexibility and control. Armeta is a team of experts with deep expertise in software development and ML/DL, with offices in Astana, San Francisco, and Doha. The technology is already in production, supporting real-world facilities and enabling more efficient engineering and compliance workflows.

Role Description

The Machine Learning will design, develop, and deploy the backend services and ML systems that power Armeta's document understanding and compliance products. Day-to-day responsibilities include building backend ML services with FastAPI, integrating LLMs, NLP, and computer vision models into applications and internal tools, and training and fine-tuning models for NLP and CV tasks. The engineer will work extensively with retrieval-augmented generation (RAG) — loading, processing, indexing, and searching data across vector and full-text stores — and with both SQL and NoSQL databases. The role involves building complete end-to-end pipelines, from data ingestion through model inference to production serving, and participating in the testing, debugging, and optimization of AI/ML features to keep them accurate, robust, and scalable. This is a full-time, on-site position located in Astana, Kazakhstan.

Qualifications

• 1–3 years of experience in ML across one or more areas: NLP, computer vision, or classic deep learning.
• Hands-on experience designing and developing microservices with FastAPI.
• Production experience with vector databases and/or full-text search engines (e.g., Qdrant, Milvus, Elasticsearch).
• Experience with one or more LLM frameworks, such as LangGraph, Haystack, or LlamaIndex.
• Experience working with multimodal LLMs (Gemini, Claude, GPT) as well as open-source models (Qwen, Gemma, and similar).
• Proficiency in Python and familiarity with common ML frameworks and libraries (e.g., PyTorch, TensorFlow, scikit-learn).
• Ability to work on-site in Astana, collaborate with cross-functional teams, and communicate technical concepts clearly.
• Familiarity with construction, engineering, or industrial domains, document processing, or information retrieval systems is a plus.