About the job
At Arkadium, we're driven by a passion for creating enjoyable experiences through gaming. For over two decades, we've developed some of the most beloved games around the globe, from the classic Solitaire on Windows to numerous titles available on Arkadium.com, iOS, Android, and major gaming platforms worldwide.
As an Evergreen company, our core values, Fierce Drive, Positive Energy, and Living Full Lives, guide our decisions and operations. We are privately held, founder-led, and take pride in being recognized as a top workplace, ensuring a stable yet dynamic growth environment.
Our accolades include recognition from 'Happiness Works' for 2023, 2024, and 2025 in Portugal, as well as 'Crain's Best Places to Work 2022' and 'Great Place to Work' in New York for 2022 and 2023!
Are you ready to join the Arkadium family? We're excited to hear from you!
Position Overview
We are seeking a passionate Data Scientist interested in exploring AI and gaming to develop practical applications of Generative AI and machine learning across our gaming platforms. In this role, you'll leverage existing Large Language Models (LLMs) and fine-tuning methodologies to demonstrate the potential of our data in enhancing AI models.
Your contributions will also include employing traditional machine learning techniques to enrich player experiences, enhance internal tools, and provide actionable insights for product and marketing teams.
Collaboration will be key as you work closely with engineers, product managers, and analysts to transform innovative ideas into scalable AI solutions that engage millions of players globally.
We welcome applicants from mid-level to senior backgrounds, provided you possess a strong enthusiasm for AI and a desire to innovate and construct impactful systems.
Key Responsibilities
- Investigate and implement Generative AI solutions utilizing existing LLMs.
- Experiment with fine-tuning and adapting models for applicable use cases.
- Employ traditional machine learning techniques to address challenges such as player behavior analysis, recommendation systems, and marketing optimization.
- Prototype and assess new AI-driven features and tools.
- Collaborate with cross-functional teams to align business needs with data science solutions.
