Senior Software Engineer, AI/ML

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience building and shipping technical products. Experience with the area of Generative AI and Large Language Models (LLM).
• Experience developing/launching products/technologies within AI/ML or a related area.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• Experience in engineering automated evaluation harnesses, reward models, or testing frameworks (e.g., LLM-as-a-judge, visual regression testing, Reinforcement Learning from Human Feedback (RLHF)) to benchmark model quality, latency, and performance.
• Experience in adapting LLMs or foundational models to comprehend spatial environments, physical constraints (e.g., gravity, momentum, collisions), and material properties.
• Expertise in optimizing memory bandwidth, Key-Value (KV)-caching, and token routine specifically to support long-context, multi-agent game loops without latency spikes.
• Foundational knowledge of 3D linear algebra, spatial reasoning, computational geometry, and real-time graphics.

About the job

Responsibilities

• Design industry-first evaluation suites and reward models to systematically quantify subjective game quality, balance, and core loop fun, while deploying autonomous multi-agent frameworks to playtest generated code and verify physical logic before release.
• Address the interactive blind spots of standard Large Language Models (LLMs) by fine-tuning models with deep domain knowledge in 3D mathematics, engine architectures, and physical reasoning building frictionless bridges directly into real-time render loops.
• Drive the foundational research and deployment of rapid-iteration generative models leveraging distillation algorithms for sub-second, transparent 2D sprite generation and adaptive-resolution Diffusion Transformers (DiTs) to generate rigged 3D meshes (using lossless O-Voxel representations).
• Design intelligent, multi-agent playtesting frameworks where autonomous AI agents simulate playthroughs of generated code and levels to verify physical logic, boundary constraints, and objective playability before human release.
• Design a foundation model for gaming.