Senior Machine Learning Engineer

PLAY, GROW and WIN To be a part of Virtuos means to be a creator.  At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004.  Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION We are seeking a Principal ML Engineer who operates with high autonomy to drive our AI systems for game development. You will operate as an Individual Contributor (IC), owning the lifecycle from experimental PoCs to production-scale deployment. This is an Applied AI role. You won't just be researching; you will integrate state-of-the-art models into tooling for artists and developers, balancing fine-tuning with inference optimization to solve real production bottlenecks. • Agent Architectures: Design and build complex agent workflows using frameworks like LangGraph/LangChain, leveraging MCP, RAG/GraphRAG, and custom skill integration. • Generative Content Pipelines: Architect Gen2D/Gen3D/video generation workflows (Stable Diffusion, Open Source LLMs) that integrate seamlessly with DCC tools and game engines. • Production Engineering: Move beyond notebooks. Build robust evaluation frameworks and deploy efficient, cost-effective systems using Python, FastAPI, AWS (SageMaker/Bedrock), and MLOps best practices. • Technical Scoping: Navigate ambiguous problems by building PoCs to validate feasibility. Collaborate with product and creative teams to translate technical constraints into realistic roadmaps. • Experience: 7+ years building production systems (ML/AI focus), with a proven track record of shipping code — or demonstrably equivalent transferable experience. • Technical Depth: Demonstrable expertise in Agent Architectures or Generative Content workflows (or both). • Comfort with Ambiguity: You don't wait for a spec sheet. You enjoy exploring a blank canvas, building a prototype, and iterating until the path forward is clear. • Pragmatism: Ability to determine when to use off-the-shelf models vs. fine-tuning vs. simple scripts. • Stack Familiarity: Strong proficiency in Python, with experience in AWS, LangChain/LangGraph, ComfyUI, or similar modern AI stacks.