Machine Learning Engineer

Absurd Ventures•Santa Monica, CA

2h•$165,000 - $200,000•Onsite

About The Position

We are seeking a Senior Machine Learning Engineer to help shape the future of content systems and real-time gameplay using cutting-edge machine learning techniques. As Senior Machine Learning Engineer, you will work alongside gameplay engineers, producers, designers, and artists to integrate intelligent, adaptive systems for our toolchain and in the realtime game. You will be a key player in evolving how our games are built and experienced.

Requirements

5+ years of machine learning experience, with at least 2 years integrating models into real-time or interactive environments.
Strong C++ programming experience.
Proficient in Python and ML libraries such as PyTorch or TensorFlow.
Familiarity with training and deploying models for real-time inference with GPU/CPU constraints in mind.
Understanding of supervised and unsupervised learning, reinforcement learning, and generative models.
Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.

Nice To Haves

Experience with the Unreal Engine toolset (Blueprints, plugins, editor scripting, etc.).
Experience building or using ML tools in a game development context.
Knowledge of generative models (e.g. Diffusion, GANs, MCPs) for workflow augmentation.

Responsibilities

Work with team leads to develop and implement a machine learning (ML) strategy to maximize the potential to enhance our workflow and game systems.
Educate the team on what is possible with ML.
Design and deploy LLM techniques, including agentic workflow and toolchain enhancements.
Build pipelines that train on gameplay data and deploy models optimized for real-time inference.
Research and implement on-device small language and other local models for scalable incorporation of ML features in the live game experience.
Partner with design and gameplay teams to prototype and test ML-powered features such as smart NPC behaviors, simulation approximation and dynamic adaptive environments.
Analyze gameplay telemetry to train models that enhance engagement, retention, and personalization.
Develop internal tools using ML to streamline workflows for production, art, animation, or audio pipelines within Unreal Engine.
Stay current with ML and real-time AI trends and ensure performance scalability across platforms.
Mentor other engineers and promote best practices in integrating ML techniques.