Senior Machine Learning Engineer

About the role

We’re looking for a Senior Machine Learning Engineer who can build large-scale systems and turn them into impactful solutions for players and the business. If designing real-time, player‑facing use cases with measurable impact at massive scale sounds exciting, this could be a great fit.

Key responsibilities

• Understand games, players, and business goals to identify high‑impact ML opportunities and build strong cross‑team relationships.
• Design and build end‑to‑end, real‑time, event‑driven ML systems from data ingestion to low‑latency serving.
• Develop and deploy ML models and decision systems that personalize player experiences across the full player journey.
• Build scalable ML platform capabilities, tools, pipelines, and APIs to enable game teams to adopt ML.
• Balance speed, robustness, experimentation, and standardisation while reducing time from idea to production.
• Operate, monitor, and optimise production ML systems for performance, reliability and scalability.
• Champion modern MLOps practices through mentorship, code reviews, documentation and guidance.
• Shape ML strategy to ensure real player and business impact and raise Supercell’s AI maturity.

Required profile

• Deep expertise in Machine Learning with a proven track record of taking ML systems into production.
• Hands‑on experience deploying ML models at large scale in high‑traffic, low‑latency environments.
• Strong software, data and ML engineering skills to design, build and maintain robust end‑to‑end pipelines.
• Experience using modern AI‑assisted development tools to accelerate iteration.
• Ability to collaborate with developers and AI agents and drive projects from idea to production.
• Excellent problem‑solving, analytical thinking and attention to detail.
• Clear communication skills for both technical and non‑technical audiences.
• Positive, proactive “can‑do” mindset with willingness to dive deep and take ownership.
• Passion for games; previous industry experience is a strong plus.

Required skills

• Python
• Databricks
• SQL
• Spark
• Redis
• Tecton
• AWS
• GCP
• PyTorch
• Ray
• TensorFlow
• ONNX
• FastAPI
• Triton inference
• Docker
• Kubernetes
• Terraform
• Kubeflow
• GitHub Actions
• Grafana
• Prometheus
• Weights and Biases
• MLflow
• Claude Code
• Codex