Machine Learning Engineer (f/m/x)

We are looking for a skilled Machine Learning Engineer to join our team in Poland, with hands-on experience in fine-tuning and deploying custom large and small language models (LLMs/SLMs) to production.

Requirements

• At least 3+ years of hands-on experience in machine learning, with a focus on NLP and language models.
• Proven experience with LLM/SLM fine-tuning, training, and optimization, including LoRA, QLoRA, or similar techniques.
• Strong understanding of transformer architectures and experience working with open-source models (e.g., Hugging Face, Mistral, LLaMA, Gemma).
• Experience designing and deploying RAG systems in production environments.
• Hands-on experience with Python, PyTorch or TensorFlow, and ML frameworks and libraries.
• Experience deploying and operating ML models in cloud environments, ideally GCP.
• Familiarity with vector databases, embedding models, and semantic search.
• Ability to bridge research and engineering: experiment fast, ship stable solutions.
• Strong English communication skills (B2/C1 or above).
• Availability to travel to our office in Gliwice, Poland, at least once a month to collaborate in person with the team.

Benefits

• Real Impact: Your work will directly power next-gen autonomous commerce experiences used by top-tier businesses.
• Cutting-Edge Technology: Work with advanced AI frameworks like LangChain and LangGraph, and bring LLM-driven features to production in a cloud-native environment.
• Autonomy and Innovation: Explore agentic AI, RAG systems, and next-gen architectures with the freedom to propose and test new ideas.
• Collaborative Culture: Join a team of talented professionals who value knowledge-sharing, open communication, and a passion for building exceptional systems.
• Impactful Contribution: Be part of a company where your work directly impacts the success of a next-generation commerce platform used by top-tier businesses.
• Flexible work setup: enjoy a remote-friendly with monthly team meetups in Gliwice, combining flexibility and well-being with meaningful in-person collaboration.