MLOps/AI Engineer/ Data Scientist

Responsibilities

• Design, develop, and productionize innovative AI and machine learning solutions
• addressing real business challenges.
• Explore and implement modern approaches across
• Python, APIs, microservices, and cloud-native technologies

Design and maintain

• ML and AI pipelines, supporting the full lifecycle from experimentation and training to deployment, monitoring, and continuous improvement.
• Build scalable, resilient, secure, and maintainable systems capable of supporting
• Collaborate with engineers, data scientists, architects, business stakeholders, and client teams to turn ideas and prototypes into reliable solutions.
• Help define and promote

Preferred

• Experience taking ML solutions beyond experimentation and into real-world applications is highly valued.
• banking, financial services, or another highly regulated industry
• Any of the following would be an advantage, but they are not required for every profile:
• Hands-on experience with frameworks and platforms such as
• LangChain, Haystack, Kubeflow, or comparable technologies.
• Experience designing
• LLM/RAG architectures, vector search, embeddings, AI agents, or GenAI applications.
• Experience with one or more major
• cloud platforms
• and cloud-native AI/ML services.
• Experience designing and developing
• microservices architectures
• MLOps frameworks and ML lifecycle best practices
• Experience deploying and operating applications or ML workloads on

Kubernetes

• DevOps, Infrastructure as Code, CI/CD, observability, and production monitoring
• Experience working with enterprise-scale data and AI environments.

DATA SCIENTIST / AI ENGINEER / MLOPS ENGINEER

• AI INFUSED. THE FUTURE IS BUILT, NOT JUST IMAGINED.
• Location: Kraków, Poland

WHY JOIN CAPCO?

You’ll join an environment where

AI meets real-world transformation

• At Capco, you can work with talented people across engineering, data, architecture, and financial services while solving challenging problems for leading organizations.
• You’ll have the opportunity to experiment, build, scale, and influence how AI is applied in practice
• whether your passion is creating intelligent models, engineering AI products, or building the platforms that make AI reliable at scale.

If you see yourself as a

Data Scientist, AI Engineer, MLOps Engineer — or somewhere at the intersection of all three — we want to hear from you.

ABOUT US

At

Capco Poland, we’re not just another consultancy — we’re helping shape the future of financial services through technology, data, and AI.

As a global technology and management consultancy, we partner with leading organizations across banking, payments, capital markets, wealth, and asset management, helping them solve complex challenges and turn ambitious ideas into real-world solutions.

Our culture is

fast-moving, flexible, collaborative, and entrepreneurial. We encourage people to challenge the status quo, experiment with new technologies, and take ownership of what they build.

As we continue to scale our AI capabilities, we’re looking for talented professionals across

Data Science, AI Engineering, and MLOps who want to design, build, and operationalize the next generation of intelligent solutions.

You don’t need to fit neatly into one box. Whether your strengths lie in developing models, engineering AI applications, or building the platforms that bring AI into production, we’d like to hear from you.

HOW YOU WILL MAKE MAGIC HAPPEN

• Depending on your experience and area of expertise, you will have the opportunity to:
• Machine Learning, Generative AI, Large Language Models (LLMs), and intelligent automation
• Build robust AI applications and services using

Develop reusable

• AI/ML libraries, frameworks, components, and common assets that accelerate AI adoption at scale.
• production-grade AI workloads

Apply modern

MLOps, DevOps, and software engineering practices to AI solutions.

Work with

Docker, Kubernetes, cloud platforms, CI/CD pipelines, model registries, monitoring, and automation tooling engineering standards, architectural principles, reusable patterns, and best practices for AI development.

Stay close to emerging AI technologies and evaluate where they can create meaningful value for our clients.

WHAT MAKES YOU AWESOME

• We’re interested in different AI profiles, so we don’t expect every candidate to have experience in everything listed below.
• We’re looking for people who bring a strong combination of skills across one or more of these areas:

Data Science & Machine Learning

• Practical experience developing and evaluating machine learning, statistical, or AI models
• Strong Python skills and experience with the modern data science and ML ecosystem.
• Understanding of model development, experimentation, feature engineering, validation, and performance evaluation.

AI Engineering

Strong

• Python and software engineering skills, including clean code, testing, design patterns, and architectural principles.
• Experience building AI-powered applications, services, or platforms.

Knowledge of

API design, microservices, distributed systems, or cloud-native application development

Hands-on exposure to

• Generative AI, LLMs, RAG, agents, or related AI architectures and frameworks is a strong advantage.
• MLOps & AI Platforms
• Experience building or operating
• ML/AI infrastructure and production pipelines
• Practical knowledge of

Docker and Kubernetes

• Experience with CI/CD, automation, model deployment, monitoring, observability, or model lifecycle management.
• Understanding of scalable, reliable, and secure production environments for ML and AI workloads.

WHAT WE VALUE ACROSS ALL PROFILES

Around

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

A university degree in

• Computer Science, Mathematics, Physics, Engineering, or another relevant discipline — or equivalent practical experience.
• Strong problem-solving skills and an engineering mindset.
• Understanding of good software engineering and application design practices
• Ability to work effectively in an

Agile, collaborative environment

• Curiosity and a strong desire to keep learning as AI technologies and engineering practices evolve.
• Ability to communicate technical ideas clearly and collaborate with both technical and non-technical stakeholders.

Experience within

is particularly welcome.

GREAT IF YOU ALSO HAVE

• Familiarity with established
• Knowledge of

ONLINE RECRUITMENT PROCESS

• Screening call with the Recruiter → Capco Hiring Manager Interview → Client Interview → Feedback / Offer
• The exact recruitment process may vary depending on the role and project.