Principal AI/ML Engineer (Gamedev)

TL;DR

Principal AI/ML Engineer (Gamedev): Designing and scaling machine learning systems for interactive entertainment with an accent on reinforcement learning, decision automation, and content production optimization. Focus on delivering production-grade ML models, building robust training/inference pipelines, and establishing engineering standards across the AI Center of Excellence.

Location: Stockholm or London

Company

hirify.global is a leading interactive entertainment company behind iconic mobile titles like Candy Crush, creating games played by over 200 million monthly active users worldwide.

What you will do

• Drive end-to-end ML delivery from problem framing through to production monitoring.
• Build and maintain scalable batch and streaming pipelines for training and inference.
• Design effective offline and online evaluation strategies to optimize game outcomes.
• Partner with product teams, designers, and data scientists to translate opportunities into reliable systems.
• Set technical standards for ML adoption and provide leadership through mentorship and architectural influence.

Requirements

• Proven track record delivering production ML systems in complex consumer-facing environments.
• Strong software engineering skills in Python with proficiency in frameworks like PyTorch or TensorFlow.
• Deep expertise in causal inference, contextual bandits, or reinforcement learning.
• Strong operational mindset regarding CI/CD, monitoring, observability, and infrastructure.
• Excellent stakeholder management and communication skills to align multidisciplinary teams.
• Strong leadership experience in coaching and mentoring junior engineers.

Nice to have

• Experience building ML tooling or platform infrastructure.
• Background in game development and understanding of player behavior analytics.
• Contributions to open-source ML projects.

Culture & Benefits

• Direct product impact by shipping ML solutions that influence millions of players.
• Opportunity to work with massive scale datasets and solve real-world constraints.
• Focus on pragmatic engineering, principled measurement, and architectural excellence.
• Collaborative environment within a central AI Center of Excellence supporting global game teams.