Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

As an MLOps Engineer, you will ensure that machine learning models are efficiently deployed, monitored and maintained across environments. Your responsibilities will include automating model deployment and updates, implementing CI/CD pipelines for ML workflows, optimizing ML models, and setting up monitoring and logging to support reliable production operations. 

You will also contribute to GenAI-ready delivery by supporting model lifecycle practices for LLM-based, RAG-based or agentic solutions where such patterns are relevant to client needs. 

Working with diverse and technically advanced solutions will allow you to build strong relationships with clients and continuously grow your expertise. You will be part of highly self-organizing, independent teams that operate in agile and lean engineering environments, fostering continuous improvement and innovation. 

Your project

Cloud & Custom Applications (C&CA) provides comprehensive end-to-end IT services from business specification, through software development and implementation, to application maintenance using leading IT technologies and management methods. 

We enthusiastically institute solutions in the fields of DevOps, SRE, broadly understood automation and AI, with a practical focus on improving delivery efficiency, quality and reliability. 

Your Tasks

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.

Your Profile

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.

What You'll love about working here

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.

Get to know us

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.

Do you want to get to know us better? Check our Instagram — @capgeminipl or visit our Facebook profile — Capgemini Polska. You can also find us on YouTube.

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com

Capgemini

Machine Learning Operations Engineer - Multiple Teams

About the Job

Requirements

Responsibilities

Desired Qualifications