Machine Learning Engineer, Memory

Overview

In this role you will advance memory-centric foundation models across modalities, partnering with researchers to design scalable architectures and production-ready systems. You will define evaluation metrics, influence roadmap decisions, and build models that effectively store, retrieve and exploit experience over long horizons. Join our Unreal Engine ecosystem to push cross-functional solutions that empower content developers worldwide and shape future AI-enabled tooling. This is a hands-on, impact-driven opportunity to influence how models reason, remember, and act at scale.

Pay / Benefits

• 100% for benefits except PMI for dependents
• pension
• private medical insurance
• health care cash plan
• dental insurance
• disability and life insurance

Responsibilities

• Design memory architectures that span problems, modalities and products
• Define metrics to evaluate memory performance
• Deliver production-ready, scalable learning models and algorithms
• Assess model effectiveness and inform the ongoing roadmap
• Collaborate with researchers and engineers to implement cross-functional solutions

Key requirements

• PhD in Computer Science, Mathematics or related field or 3+ years of industry experience
• Experience building ML algorithms for vision and/or language and deploying them in production
• Expertise with foundational models and vision and/or language, including local deployment and post-training with open weights
• Knowledge of memory, state, or long-horizon behavior in foundation models
• Proficiency in Python and ML libraries (numpy, scipy, sklearn, pytorch)
• Experience working collaboratively in an agile environment

• collaboration
• adaptability
• effective communication
• Foundational models
• Vision and/or language ML
• Memory / long-horizon modelling

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