Machine Learning Engineer

Opis oferty

Matrix Eastern Europe, the offshore division of Matrix IT, one of the leading global R&D services companies with more than 10,000 professionals, is looking for an AI Senior Software Engineer to join one of our teams -Stampli!

We’re hiring a Machine Learning Engineer to accelerate AI-driven innovation across our B2B SaaS product and the broader Stampli organization.

This is a hands-on, end-to-end development role where you’ll lead the implementation of ML/LLM-based solutions that boost operational efficiency and deliver exceptional product experiences. As an AI-First company, Stampli embed AI across every department and workflow—you’ll be at the heart of this transformation.

You will collaborate closely with product managers, engineers, and stakeholders to identify impactful AI opportunities, build state-of-the-art systems, and scale them across the organization.

Wymagania

• 6+ years of experience as a Backend Developer, Data Engineer, or ML Engineer
• Bachelor’s degree in Computer Science or a related STEM field
• Strong proficiency in Python and ML tooling
• Proven ability to build production-grade ML systems end-to-end
• Deep experience with LLMs and ML frameworks (e.g., LangChain, LangGraph, Hugging
  Face, TensorFlow, PyTorch)
• Solid foundation in system design, architecture, and microservice patterns
• Excellent problem-solving skills and ownership mindset
• Strong collaboration and communication abilities

Zakres obowiązków

• Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve
• real-world challenges across Stampli’s product and internal workflows.
• Own Full Lifecycles: Take projects from concept all the way to production, including
• model training, evaluation, integration, and monitoring.
• Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging
• Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
• Collaborate Cross-Functionally: Partner with product managers, engineers, and
• stakeholders to embed AI capabilities into user-facing features and backend services.
• Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in
• CI/CD, observability, and cloud infrastructure.
• Report with Impact: Share progress, challenges, and results clearly with technical and
• executive stakeholders.