ML Engineer (LLMs & Agentic AI)

UST Global is seeking a skilled ML Engineer with experience in Large Language Models (LLMs), generative AI, and agentic architectures to join our growing R&D and Applied AI team. You will work closely with AI/ML researchers, data engineers, and product teams to design, implement, and optimize models that power autonomous exception resolution, anomaly detection, and explainable insights. This is a hands-on engineering role where you will not only build and scale ML systems but also actively contribute to cutting-edge applied research in agentic AI.

Location: Ukraine/Poland.

Working hours: 17:00 – 01:00 Ukrainian time, 16.00-24.00 Polish time.

Required Qualifications:

• 3+ years of experience building and deploying ML systems.
• Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, and Hugging Face Transformers.
• Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference optimization).
• Familiarity with vector databases, embeddings, and RAG pipelines.
• Ability to work with structured and unstructured data at scale.
• Knowledge of SQL and distributed data frameworks (Spark, Ray).
• Strong understanding of ML lifecycle: data prep, training, evaluation, deployment, monitoring.
• Demonstrated experience with at least two of the following ecosystems: OpenAI GPT models (chat, assistants, fine-tuning), Anthropic Claude (safety-first AI for reasoning and summarization), Google Gemini (multimodal reasoning, enterprise-scale APIs), Meta LLaMA (open-source, fine-tuned models).

Preferred Qualifications:

• Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen).
• Knowledge of AI safety, guardrails, and explainability techniques.
• Hands-on experience deploying ML/LLM solutions in cloud environments (AWS, GCP, Azure).
• Experience with CI/CD for ML (MLOps), monitoring, and observability.
• Familiarity with anomaly detection, fraud/risk modeling, or behavioral analytics.
• Contributions to open-source AI/ML projects or publications in applied ML research.

We offer:

• Friendly professional staff and a warm atmosphere.
• The environment where you can implement your ideas.
• Paid vacations and sick leaves.
• Medical insurance.
• Opportunity to work remotely.
• Participation in educational activities and thematic conferences.
• Team parties and corporate events.