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EGego logo

ego

Location not stated

Member of Technical Staff.

FULL TIMEDATA & ML
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Careers / Open role

Member of Technical Staff

Research Full-time San Francisco, CA

The Role

We're seeking an exceptional AI researcher/engineer to join our team in developing the ego game agent architecture — a groundbreaking system for autonomous gameplay in 3D environments. This role combines cutting-edge research with practical engineering to create AI agents capable of human-level reaction times (300–500ms) in complex game worlds.

Working with our team and researchers from AI Singapore and NTU's Prof. Bo An's Lab, you'll help architect a hierarchical AI system that combines high-level reasoning using multimodal LLMs with fast, low-level action models. The ideal candidate brings deep expertise in computer vision, transformer architectures, and real-time AI systems, along with practical experience shipping production ML systems.

This role represents a unique opportunity to push the boundaries of AI gaming, building on projects like Minecraft Voyager while working within our game development ecosystem. You'll collaborate closely with our engineering team to integrate these AI systems seamlessly into our game engine, while conducting novel research that advances the field of autonomous game AI.

If you're passionate about combining research-grade AI with practical engineering to create autonomous agents that can truly play games like humans do, we'd love to hear from you.

What you'll build

  • Real-time perception systems using state-of-the-art computer vision models
  • Fast vision-language-action models inspired by robotics approaches
  • Efficient model architectures that achieve human-level reaction times
  • End-to-end autonomous gameplay across various 3D games

Key Responsibilities

  • Develop and implement hierarchical AI architectures combining high-level reasoning and low-level action models
  • Design and optimize real-time computer vision systems for game object detection and tracking
  • Create and fine-tune vision-language-action models for autonomous gameplay
  • Collaborate with AI Singapore and NTU researchers on cutting-edge AI agent architectures
  • Implement and optimize GUI interaction models and 3D object tracking systems
  • Contribute to data collection, model training, and benchmark development
  • Work closely with game developers to integrate AI systems into the game engine

Required Qualifications

  • Master's or PhD in Computer Science, AI, or related field
  • Strong programming skills in Python and experience with deep learning frameworks such as PyTorch
  • Expertise in computer vision and transformer architectures
  • Experience with real-time AI systems and optimization
  • Practical knowledge of LLMs and vision-language models
  • Background in reinforcement learning or imitation learning
  • Familiarity with game engines and 3D environments
  • A strong interest in video games and a desire to contribute to the future of interactive entertainment
  • Strong communication and collaboration skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
  • Ability to self-manage and work independently or collaboratively as needed

Preferred Skills (Nice to Have)

  • Experience with vision-language-action models (VLA)
  • Knowledge of model distillation and optimization techniques
  • Familiarity with YOLO, SAM, or similar computer vision frameworks
  • Experience with behavior cloning and inverse dynamics models
  • Background in game development or 3D graphics
  • Publication record in relevant conferences (ICLR, NeurIPS, ICML, etc.)
  • Top 500 on Overwatch
  • Has seen all X Fast and Furious movies

Project Highlights

  • Developing real-time AI agent architectures with 300–500ms latency
  • Implementing multi-modal LLM systems for game understanding
  • Creating efficient vision-language-action models
  • Building scalable data collection and training pipelines
  • Benchmarking across various 3D games and environments

Got what it takes?

In your application we want to see your personal style — what makes you tick and why you think your next opportunity is here with us.

Prefer email? Send your application and resume to [email protected].

Pay
Not stated
Where
Not stated
Work
Not stated
Type
Full time
Posted
29 Oct, 2026
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