UST
ML Engineer (LLMs & Agentic AI)
USTUkraine11 hours ago
Full-timeRemote FriendlyEngineering

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.

Key Skills

Ranked by relevance