Enterprise · Game engine
Currently tracking 38 active AI roles, down 39% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $100k–$300k (avg $197k).
Unity has 49 active AI-related job listings. The majority of these roles are focused on agents, representing 35% of the total. Engineering is the dominant function, with 46 positions. The United States is the primary hiring country, accounting for 37 of the listings. Frequent tech tags include model_serving, recommender_systems, and agent_orchestration. In the last 30 days, there were 0 new AI roles posted, a 100% decrease compared to the prior 30 days.
Unity currently has 49 active AI-related roles in our index. The most common open titles are: Senior Machine Learning Engineer, Advertiser Growth (4), Staff Machine Learning Engineer, ML Infrastructure (4), Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD) (3), Senior Machine Learning Infrastructure Engineer (3), Staff Software Engineer, Feature Platform (3). Most positions are in Engineering and Research.
Unity's active AI hiring is concentrated in: agents (35%), serving infrastructure (27%), data (22%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Unity is hiring AI talent in: United States (37 roles), China (5 roles), Canada (4 roles), Israel (3 roles).
Job postings at Unity most frequently mention: Performance Optimization, A/B Testing, Model Monitoring, Data Pipelines, Apache Airflow.
In the past 30 days, Unity has posted 0 new AI-related roles. That is a -100% change versus the prior 30 days (9 → 0).
| Title | Stage | AI score |
|---|---|---|
| Senior/Staff Machine Learning Engineer, Data Infrastructure This role focuses on building and evolving a large-scale offline data platform for Unity, specifically for generating data infrastructure, training datasets, and orchestrating data workflows. The engineer will work with ML engineers and platform teams to ensure pipelines are reliable, scalable, and efficient for growing data volumes and complex training workloads, playing a key role in preparing model datasets for production ML systems. | Data | 7 |
| Staff Machine Learning Engineer, ML Infrastructure - Online Staff ML Engineer focused on building and operating the online ML inference platform at Unity. This role involves designing, optimizing, and scaling infrastructure for serving production ML models with low latency and high reliability, supporting experimentation, and improving observability. The focus is on the infrastructure that enables ML models to be deployed and run efficiently in a production environment. | Serve |
| 7 |
| Staff Machine Learning Engineer, ML Infrastructure - Offline Staff ML Engineer focused on building and evolving the large-scale offline ML platform for data generation, workflow orchestration, and distributed model training at Unity. | Data | 7 |
| Senior Machine Learning Engineer, ML Infrastructure - Online Senior/Staff ML Engineer to design and evolve Unity Vector’s online model inference platform. Focuses on building reliable infrastructure for serving ML models in production, optimizing inference performance, and enabling safe, efficient experimentation across high-traffic online systems. Requires strong systems thinking, deep experience with production ML infrastructure, and ability to drive architectural improvements. | Serve | 7 |
| Senior Machine Learning Engineer, ML Infrastructure - Offline Senior ML Engineer focused on building and operating a large-scale offline ML platform for Unity. The role involves designing and evolving data pipelines for training datasets, orchestrating ML workflows, and enabling efficient, distributed model training. Key responsibilities include developing infrastructure for distributed training, integrating with orchestration systems, and optimizing performance. | DataServe | 7 |