MLOps Engineer (Machine Learning, MLFlow, Kubernetes, DVC)

Our requirements

• Master’s, engineer’s or bachelor’s degree.
• At least 4 years of experience in CI/CD and/or cloud technologies.
• Experience with Git, CI/CD tools, Kubernetes, Docker, ML frameworks such as TensorFlow or similar, monitoring and logging tools, and Infrastructure as Code.
• Practical experience with MLflow, DVC or similar tools supporting model lifecycle management will be an advantage.
• Hands-on experience in AI / GenAI, including practical use of LLMs, RAG patterns and agentic workflows in production or near-production environments, will be an advantage.
• Knowledge of vector search, embeddings, model-serving patterns or AI observability will be an advantage.
• Good written and verbal communication skills, minimum B2 English.

Your responsibilities

• Ensure that machine learning models are efficiently deployed, maintained and monitored across environments.
• Automate deployment and update processes for machine learning models.
• Implement CI/CD pipelines for ML models and ML workflows.
• Set up monitoring, logging and observability for ML models and model-serving platforms.
• Optimize ML models and model delivery processes for production or near-production environments.
• Support AI and GenAI initiatives, including LLM-based solutions, RAG patterns and agentic workflows where relevant.
• Help establish reliable MLOps practices for model versioning, reproducibility, governance and responsible AI delivery.

About the project

What we offer

• Practical benefits: private medical care with Medicover with additional packages (e.g., dental, senior care, oncology) available on preferential terms, life insurance and 40+ options on our NAIS benefit platform, including Netflix, Spotify or Sports card.
• Access to over 70 training tracks with certification opportunities (e.g., GenAI, Architects, Google) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, TED Talks and Udemy Business materials and trainings.
• Enjoy hybrid working model that fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home, thanks to home office package (including laptop, monitor, and chair). Ask your recruiter about the details.
• Community Hub that will allow you to choose from over 20 professional communities that gather people interested in, among others: Salesforce, Java, Could, IoT, Agile, AI.

Benefits

• private medical care
• sharing the costs of foreign language classes
• sharing the costs of professional training & courses
• life insurance
• flexible working time
• integration events
• corporate sports team
• no dress code
• parking space for employees
• extra social benefits
• sharing the costs of tickets to the movies, theater
• redeployment package
• christmas gifts
• employee referral program
• charity initiatives
• free chat/call with a therapist

Recruitment stages

• 1.
  Interview with the recruiter
• 2.
  Competency Tests/Language Verification
• 3.
  Video call with a manager
• 4.
  Final Decision

Capgemini Polska