Lead Machine Learning Engineer

The Role We are seeking a Lead 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.

Key Responsibilities

• 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.

Qualifications

• 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.