Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building the algorithmic core of an AI-native platform research project with an accent on LLMs, Knowledge Graphs, semantic search, and multi-agent orchestration. Focus on AI agent integration with Knowledge Graphs and developing models supporting real-time context brokering.

Location: Ability to work from Białystok or surrounding areas; hybrid work model required (at least 3 days in the office + max 2 days remote per week).

Salary: PLN 20,000–25,000 per month (net B2B) or employment contract (gross).

Company

hirify.global builds innovative digital products for the modern workplace in the Cloud.

What you will do

• Design and implement algorithms for the MCP Graph Broker.
• Conduct research on AI agent integration with Knowledge Graphs and develop models supporting real-time context brokering.
• Drive innovation and continuous improvement in our technology practices.
• Utilize your extensive knowledge of cloud computing, system integration, and software development.

Requirements

• At least 5 years of experience in a senior or lead role in cloud solutions architecture.
• A solid understanding of Azure cloud services, microservices, and API management.
• Knowledge of the MCP (Model Context Protocol) protocol or similar context protocols, and practical use of machine learning tools/ML/AI APIs in production environments.
• Knowledge of vector databases and semantic search techniques (e.g., Azure AI Search) in the context of RAG (Retrieval-Augmented Generation) systems.
• Experience with multi-tenant architecture – designing context separation, data isolation, and access policies in SaaS environments.
• Fluency in Polish (C1+) and English (B2+), both spoken and written.

Nice to have

• Experience with enterprise system integration via API (Microsoft 365 Graph API, ServiceNow REST API) in the role of connector or MCP integration developer.
• Knowledge of MLOps – deploying and monitoring models in production using Azure ML and CI/CD pipelines.
• Experience with multi-agent systems at enterprise scale.
• Knowledge of machine learning methods, with particular emphasis on NLP and LLM-based systems.

Culture & Benefits

• Work and professional development while building a distributed enterprise-class cloud system based on AI as infrastructure.
• Direct impact on the architecture of a platform used by hundreds of thousands of employees.
• Opportunity to explore Azure infrastructure solutions, the latest LLMs, and MLOps tools.
• Multi-directional professional development, certifications, and knowledge sharing.
• Flexible work model (hybrid).
• Benefits package (private healthcare, Multisport card).