MLOps Engineer

Quick Facts

• Role: MLOps Engineer (AI/ML)

• Location: Kraków, Poland

Description

You will design, develop, and productionize AI and machine learning solutions, bringing them from experimentation to reliable, production-grade applications. The role focuses on ML/AI pipelines, AI platform engineering, and applying modern MLOps/DevOps practices for scalable, secure, and maintainable workloads. You will collaborate with engineers, data scientists, architects, and business stakeholders to turn prototypes into operational solutions.

Responsibilities

• Design, develop, and productionize AI/ML solutions for business problems

• Implement modern ML approaches including Machine Learning, Generative AI, LLMs, and intelligent automation

• Build AI applications and services using Python, APIs, microservices, and cloud-native technologies

• Develop reusable AI/ML libraries, frameworks, and components

• Design and maintain ML/AI pipelines across the full lifecycle (training, deployment, monitoring, improvement)

• Apply MLOps, DevOps, and software engineering practices to AI solutions

• Work with Docker, Kubernetes, cloud platforms, CI/CD, model registries, monitoring, and automation tooling

• Collaborate across engineering and data teams to deliver reliable solutions

• Help define engineering standards, architecture principles, reusable patterns, and best practices

• Stay current with emerging AI technologies and evaluate value for clients

Requirements

• 4+ years of professional experience in software engineering, data science, machine learning, MLOps, AI engineering, or a related area

• Degree in a relevant field (Computer Science, Mathematics, Physics, Engineering) or equivalent practical experience

• Strong problem-solving skills and an engineering mindset

• Strong software engineering and application design practices

• Ability to work effectively in an Agile, collaborative environment

• Curiosity and willingness to keep learning as AI technologies evolve

• Ability to communicate technical ideas clearly with technical and non-technical stakeholders

• Experience in banking/financial services or other highly regulated industries (welcomed)

Benefits

• Opportunity to experiment, build, scale, and influence how AI is applied in practice

• Work with talented teams across engineering, data, architecture, and financial services

• Build and operationalize next-generation intelligent solutions

• Entrepreneurial, flexible, collaborative culture with ownership of what you build