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 |
| ML Infrastructure Engineer - (Early Career/Internship) ML Engineer role focused on building and maintaining the offline ML platform infrastructure for data pipelines, distributed model training, and ML workflows. This role supports large-scale model training, feature generation, and experimentation, bridging research and production at scale. | Data |
| 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 - 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 |
| Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD) Machine Learning Engineer focused on building and maintaining the offline ML platform infrastructure for data pipelines, distributed model training, and ML workflows at Unity. | Data | 7 |
| Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD) Machine Learning Engineer focused on building and maintaining the offline ML platform infrastructure for data pipelines, distributed training workflows, and ML pipelines at Unity. This role is for a recent PhD graduate interested in applying research to large-scale systems. | Data | 7 |
| Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD) Machine Learning Engineer focused on building and maintaining the offline ML platform infrastructure for data pipelines, distributed training workflows, and ML pipelines at Unity. This role is for a recent PhD graduate interested in applying research to large-scale systems. | Data | 7 |
| Staff Machine Learning Engineer, ML Infrastructure Staff ML Engineer focused on building and operating a large-scale offline ML platform for data generation, feature engineering, and distributed model training at Unity. | Data | 7 |
| Staff Machine Learning Engineer, ML Infrastructure Staff ML Engineer focused on building and operating a large-scale offline ML platform for Unity, supporting data pipelines, distributed model training, and experimentation workflows. | Data | 7 |
| Staff Machine Learning Engineer, ML Infrastructure Staff ML Engineer focused on building and evolving a large-scale offline ML platform for data pipelines, distributed model training, and feature generation at Unity. | Data | 7 |
| Staff Machine Learning Engineer, ML Infrastructure Staff ML Engineer focused on building and evolving a large-scale offline ML platform for data pipelines, distributed model training, and feature generation at Unity. | Data | 7 |