Senior Machine Learning Engineer

Eagle Eye Staffing Solutions

Kraków

Hybrid

PLN 180,000 - 280,000

Full time

5 days ago
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Job summary

Eagle Eye Staffing Solutions is seeking a hands-on Senior Machine Learning Engineer in Kraków for a hybrid role (3 days in the office). The position offers an Employment contract (UoP) and involves designing and implementing classical ML models, building LLM-based workflows, and contributing to reproducible ML pipelines and cloud-based solutions.

You will work in a small, experienced team with a production mindset and strong software engineering practices, contributing code and collaborating

Qualifications

  • Hands-on ML with practical modelling and evaluation.
  • Experience with AI agents or agentic workflows.
  • Experience with cloud providers (GCP/AWS/Azure).
  • Strong software engineering and production mindset.
  • Ability to write and discuss code clearly.

Responsibilities

  • Design and implement classical ML models.
  • Build reliable LLM-based workflows and AI agents.
  • Contribute to reproducible ML pipelines.
  • Develop cloud-based ML solutions.

Skills

Practical ML
Statistical modelling
AI agents
Cloud platforms
Software engineering
Code proficiency

Job description

Senior Machine Learning Engineer | Kraków | Hybrid: 3 days per week in the office Employment contract (UoP) We are looking for a hands‑on Senior Machine Learning Engineer to join a small, experienced team developing production‑ready AI and machine learning solutions. You will design and implement classical ML models, build reliable LLM-based workflows and AI agents, and contribute to reproducible ML pipelines and cloud-based solutions.
  • Practical machine learning and statistical modelling skills
  • Knowledge of AI agents or agentic workflows
  • Experience with GCP, AWS or Azure
  • Strong software-engineering and production mindset
  • Ability to write and discuss code confidently
  • GCP experience is advantageous but not mandatory.
  • 90-minute technical interview with a straightforward live-coding exercise
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