Senior Software Engineer, Machine Learning, Platforms and Devices

Google Google · Big Tech · Bengaluru, Karnataka, India

Senior Software Engineer on the Platforms and Devices team, focusing on building AI-driven evaluation suites, reward models using RLHF, and multi-agent frameworks for playtesting. The role involves fine-tuning LLMs with domain knowledge in 3D mathematics and physics, and building asset generation pipelines using distillation and DiT models for 2D/3D assets.

What you'd actually do

  1. Design industry-first evaluation suites and reward models using Reinforcement Learning from Human Feedback (RLHF) and gameplay telemetry 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.
  2. Address the spatial and interactive blind spots of standard Large Language Model (LLMs) by fine-tuning models with deep domain knowledge in three-dimension (3D) mathematics, engine architectures (e.g., Unity, Godot, Unreal), and physical reasoning (e.g., gravity, momentum, collisions), building frictionless bridges directly into real-time render loops.
  3. Build high-efficiency two-dimension (2D)/3D asset pipelines using fast distillation and DiT models to instantly generate sprites and rigged 3D meshes.
  4. Build multi-agent Artificial Intelligence (AI) frameworks to automatically playtest generated levels for physics errors, boundary bugs, and overall playability.

Skills

Required

  • Machine Learning
  • Artificial Intelligence
  • data structures
  • algorithms
  • software design
  • Reinforcement Learning from Human Feedback (RLHF)
  • multi-agent systems
  • LLM fine-tuning
  • 3D mathematics
  • game engine architectures
  • physical reasoning
  • 2D/3D asset generation
  • distillation models
  • DiT models

Nice to have

  • Bachelor’s degree or equivalent practical experience
  • Unity
  • Godot
  • Unreal

What the JD emphasized

  • 5 years of experience in Machine Learning or Artificial Intelligence
  • multi-agent frameworks
  • fine-tuning models
  • asset pipelines

Other signals

  • multi-agent systems
  • RLHF
  • fine-tuning LLMs
  • asset generation