Mid Data Scientist / AI Engineer

Job Title : Data Scientist / AI engineer

Team : AI experimentation and execution (New Department)

Seniority : Mid-level

Location : Warsaw, Poland 🌎

Type : Full-time

Type of contract : B2B

About the project📝

At Sanoma Learning, we believe in the transformative potential of AI. That’s why we’ve recently established a new department : AI Experimentation & Execution .

This team is dedicated to developing early-stage AI prototypes to explore innovative solutions and accelerate experimentation across our organization.

Role responsibilities

div class="ReactFieldEditor-core display ReactFieldEditor-TextMultiLine" style="text-align : justify;" tabindex="0" role="textbox" aria-readonly="true" aria-label="Role responsibilities, The Data Scientist / AI Engineer will contribute to advancing AI experimentation at Sanoma Learning. Reporting to the Senior Director, Head of Data and AI, this role focuses on creating prototypes (PoCs / MVPs) using cutting-edge AI tools – especially in the domain of Generative AI and LLMs. The role involves translating business needs into well-scoped AI experiments, building functional prototypes, and collaborating with cross-functional teams including product owners, engineers, project managers, and analysts across Sanoma Learning’s operating companies. This is a hands-on position well suited for a technically capable and curious AI engineer who thrives on experimentation and iteration and is eager to turn new ideas into tangible value. Key Responsibilities

• Design and develop PoCs and MVPs using modern AI techniques, with focus on Generative AI, LLMs, and agent-based systems.
• Collaborate with product and experimentation teams to translate business ideas into AI prototypes.
• Work across the technical stack – from data preprocessing to model implementation, orchestration, and deployment.
• Build retrieval-augmented generation (RAG) pipelines leveraging Sanoma Learning’s proprietary content.
• Apply prompt optimization and performance tuning to ensure efficient model usage and optimize costs
• Contribute to MLOps practices including model versioning, CI / CD, and testing pipelines.
• Ensure compliance with data privacy standards in close collaboration with security and legal teams.
• Document solutions and share learnings, contributing to internal best practices and experimentation infrastructure.
• Stay up to date with the evolving AI ecosystem and bring in relevant tools and techniques. , press enter to edit.">

As Data Scientist / AI Engineer you will contribute to advancing AI experimentation at Sanoma Learning. Reporting to the Senior Director, Head of Data and AI, this role focuses on creating prototypes (PoCs / MVPs) using cutting-edge AI tools – especially in the domain of Generative AI and LLMs.

The role involves translating business needs into well-scoped AI experiments, building functional prototypes, and collaborating with cross-functional teams including product owners, engineers, project managers, and analysts across Sanoma Learning’s operating companies.

This is a hands-on position well suited for a technically capable and curious AI engineer who thrives on experimentation and iteration and is eager to turn new ideas into tangible value.

Key Responsibilities

Must-have requirements

div class="ReactFieldEditor-core display ReactFieldEditor-TextMultiLine" tabindex="0" role="textbox" aria-readonly="true" aria-label="Must-have requirements, Education

Education :

Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Data Science, Engineering, or a related technical field.

Relevant certifications in AI / ML, cloud platforms, or MLOps are a plus.

Experience :

3–5 years of hands-on experience in AI engineering, machine learning, or applied data science roles.

Experience developing PoCs or MVPs using LLMs, transformers, or related GenAI techniques.

Familiarity with RAG systems and vector databases

Exposure to cloud-native tools and infrastructure (e.g., AWS, GCP, Azure), Docker / Kubernetes, and orchestration tools like Airflow or Prefect.

Experience implementing or adapting LLM evaluation frameworks is a plus.

Understanding of compliance and governance requirements (e.g., GDPR, responsible AI practices).

Prior exposure to EdTech or publishing is beneficial but not required.

Skills :

Solid understanding of transformer-based models and prompt engineering techniques.

Proficiency in Python and experience with libraries such as LangChain, LangGraph, or OpenAI / Anthropic APIs.

Familiarity with vector databases, embedding pipelines, and chunking strategies.

Ability to develop agentic workflows and multi-step AI task execution.

Working knowledge of MLOps, version control, and model deployment pipelines.

Strong analytical thinking and experimentation mindset.

Comfortable working in agile, cross-functional environments, with good written and verbal communication skills.

Curious, adaptable, and eager to learn and implement new technologies in a fast-evolving space.

Personal Attributes :

Data-driven decision-making approach

Proactive and positive “can-do” attitude, demonstrating initiative and resilience.

Strong organizational skills, adept at managing multiple tasks simultaneously.

Self-motivated, consistently seeking opportunities for improvement and innovation.

Passionate about opportunities in Data and AI space

English at the full working proficiency (B2 / C1 level)