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

Miejsce pracy: Gdańsk

Technologies we use

Expected

Git
Kubernetes
Docker
TensorFlow

Optional

Git
Kubernetes
Docker
TensorFlow
Django

Operating system

Linux

About the project

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 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.

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.

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

Interview with the recruiter
Competency Tests/Language Verification
Video call with a manager
Final Decision

Capgemini Polska

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.

Twoje dane osobowe są u nas bezpieczne. Ochrona danych osobowych jest jedynym z naszych najważniejszych priorytetów. Przetwarzamy je w sposób odpowiedzialny, ograniczamy gromadzenie i dostęp do nich, w szczególności w odniesieniu do osób, które uczestniczyły w obecnych lub będą uczestniczyć w przyszłych procesach rekrutacji. Przygotowaliśmy dla Ciebie informację o celach i zasadach przetwarzania przez Capgemini Polska Sp z o. o. danych osobowych oraz przysługujących Ci prawach. Komplet informacji znajdziesz pod niniejszym adresem strony internetowej:

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

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