Senior Principal AI​/ML Engineer

Candy Crush Saga | King

Craft: Data, Analytics & Strategy

Are you motivated by building the shared decisioning foundations for how a live game learns, experiments, and adapts at scale? Join King as a Senior Principal AI/ML Engineer in the Decision Automation team for Candy Crush Saga
. In this role, you will help turn fragmented AI/ML and decisioning approaches into scalable, production-grade systems that support faster experimentation, safer adaptation, and more coherent player experiences across the game. This is a hands‑on senior technical leadership role
. You will shape direction through architecture, code, prototyping, design reviews, and deep technical judgment. We seek someone who can build, simplify, and connect complex systems across team boundaries.

You’ll join the Decision Automation team within Candy Crush Saga: a cross‑functional AI/ML team working closely with product, analytics, engineering, game teams, and central platform partners to enable faster, smarter, and more player‑centric decisions across the game. Our mission is to accelerate Candy’s learning loop by automating insight generation, experimentation, and adaptation s role is central to defining and building the shared architecture needed to make decision automation more scalable, reliable, and reusable across Candy.

• Causal inference and simulation capabilities usable by product teams
• Generalized automated decisioning systems across multiple game features
• Orchestration across ML systems to reduce conflicting treatments and coordination overhead

With hundreds of millions of players, the systems you help shape will operate at significant scale and influence core player‑facing decisions across Candy Crush Saga.

• Influence technical direction across Candy Crush Saga in AI/ML and decisioning through credibility, clarity, and delivery
• Stay hands‑on through meaningful production coding, technical prototyping, and implementation work on critical paths
• Set a high bar for production AI/ML engineering, including reliability, observability, maintainability, and quality of execution
• Mentor senior engineers and raise the standard of technical judgment, design quality, and cross‑team collaboration
• Lead the shared architecture for AI/ML and automated decisioning systems used across multiple components in Candy Crush Saga
• Help unify fragmented approaches into reusable technical foundations that improve consistency, speed, and scalability
• Partner with product and game teams to turn high‑value opportunities into reusable capabilities rather than one‑off solutions

• Deep experience building and shipping production AI/ML systems with meaningful business impact
• Strong applied expertise in areas such as personalization and causal inference
• Track record of connecting AI/ML methodology with real production guardrails, constraints and operational use

• Proven ability to influence technical direction across teams through credibility, clarity, and execution
• Experience defining shared patterns, technical standards, or architectural direction in complex environments
• Ability to lead senior‑level technical discussions with substance and precision

• Excellent communication skills, with the ability to explain complex technical ideas clearly to both technical and non‑technical audiences
• Proven ability to influence across departments and align teams around shared technical direction
• Strong mentoring capability, especially with senior engineers and technical leaders
• Comfortable representing technical work in high‑visibility forums, internally and externally

• Able to shape product bets through technical insight and co‑create reusable capabilities with cross‑functional partners
• Effective working across engineering, analytics, product, and platform teams
• Strong judgment in translating business goals into scalable technical systems

• Experience with large‑scale experimentation platforms, personalization systems, or decisioning infrastructure
• Familiarity with game technology, player‑facing optimization, or content adaptation systems
• Experience reducing fragmented or bespoke ML workflows into shared technical foundations

• Stockholm, Barcelona and London