Senior AI/Machine Learning Engineer, Minecraft

• Design, build, and productionize AI/GenAI services and platform components for internal and player‑facing experiences across Minecraft and other titles
• Create reusable AI building blocks and reference integrations to accelerate teams and drive studio‑wide AI enablement
• Own cloud infrastructure & MLOps: data pipelines, training/evaluation, deployment, monitoring, and operational support
• Improve reliability, performance, and cost with guardrails, fallback paths, SLOs, and actionable runbooks
• Engineer for security, privacy, and compliance through secure data access patterns and threat modeling
• Embed responsible AI principles (fairness, transparency, player safety) into system design and operations
• Collaborate cross‑discipline to solve product problems and deliver measurable business/player impact
• participate in design/code reviews and pair programming
• Document and communicate: share learnings to upskill the studio and present findings/opportunities to leadership
• Embody our Culture & Values

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
• OR equivalent experience
• Experience in AI/ML principles, frameworks, and tools (e.g., PyTorch, Generative AI, RAG)
• Experience with big data technologies like Spark (PySpark) and Databricks
• Skilled in Python (C#/TypeScript a plus)
• Familiar with modern dev practices (Agile, GitHub, Azure DevOps)
• Familiar with designing, deploying, and monitoring cloud infrastructure for AI systems
• Familiar with multiple data modalities and ML domains: computer vision, audio, predictive modeling, NLP, time series forecasting, graph networks, deep learning, and reinforcement learning
• Verbal and written communication skills
• Ability to translate complex technical concepts into clear, actionable insights for non-technical stakeholders

Games industry knowledge