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Staff Software Engineer, Engine & Tools

Riot Games•The Rocks, Sydney
Full-time7-15
AUD 180 - AUD 240/hr
👁️ 0 views•📝 0 applications•Posted 10/27/2026•Expires 11/26/2026
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Job Description

Job Type: Permanent position | Full time positionJob Description As a Staff Software Engineer, Engine & Tools on an unpublished R&D product, you will be responsible for designing and implementing AI/ML driven tools and features. You will work closely with designers, producers, and other engineers to understand their needs, and will be hands‑on in conceptualizing, planning, implementing, and maintaining AI‑powered solutions to increase developer efficiency. We’re looking for someone who is passionate about empowering their team to deliver great player experiences, works well in cross-disciplinary teams, is aware of the latest trends, and finds practical applications of AI/ML technologies to current and future development challenges. Riot engineers bring deep knowledge of specific technical areas but also value the opportunity to work in a variety of broader domains. As a Staff Software Engineer, you’ll drive important features and provide other engineers with a clear illustration of extraordinary engineering. We work with both new and current technology, creating innovative solutions to overcome high-volume obstacles and to deliver player value. You will report to an Engineering Manager supporting the Tech Foundations team within an unpublished R&D product. This is a full‑time role, based in Sydney, Australia. Internal Job Title: Software Engineer III. Responsibilities: Work closely with designers, artists, and other engineers to discover and conceptualize opportunities for AI‑powered workflow enhancements Partner with engineering leaders to help define the team’s future vision for AI‑based developer tooling and workflows Lead the application of AI/ML systems to solve developer and player facing problems Architect and help implement the foundational elements of the game’s tools ecosystem Collaborate with artists, designers, QA, and fellow engineers to scope, architect, implement, and test AI/ML‑based solutions Keep up with technical developments in the industry relating to AI/ML and find practical applications that help solve the team challenges Partner with central teams to share AI‑based solutions across Riot’s portfolio Model the team’s best practices for tools architecture and implementation Mentor engineers across multiple levels as the team scales, and provide feedback that supports their technical growth Support and advance the team’s adoption of AI/ML tools for game development through mentorship, documentation, and advocacy Provide documentation and trainings on new tools and workflows to internal customers Required Qualifications: 8+ years (or equivalent depth) of professional experience in software engineering, including experience delivering live or shipped products at scale 3+ years (or equivalent depth) working on game development tools & C++ Experience in Unreal Engine and awareness of upcoming tools in game development Experience working with AI/ML systems in a production‑ready environment B.S. in computer science or equivalent experience Proven ability to navigate ambiguity and influence cross‑functional stakeholders using strong communication skills across technical and non‑technical audiences Desired Qualifications: Applied knowledge in one or more of the following: reinforcement learning, imitation learning, decision‑making under uncertainty, LLM, AI planning, or multi‑agent systems Experience working with modern ML/data science libraries and frameworks such as PyTorch/TensorFlow, pandas, etc. Deep knowledge tooling utilized in AAA games & how they integrate with both client and backend systems. Experience developing AI‑or ML‑driven content tools that integrate with art pipelines (e.g. Maya, Blender, etc.) Experience mentoring technical leaders and contributing to engineering culture, across distributed teams #J-18808-Ljbffr

Required Skills

C++Unreal EngineAI/ML systemssoftware engineeringgame development toolsreinforcement learningimitation learningdecision-making under uncertaintyLLMAI planningmulti-agent systemsPyTorchTensorFlowpandasAAA games toolingMayaBlender

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