Currently tracking 35 active AI roles, down 46% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $100k–$300k (avg $197k).
Unity has 38 active AI-related job listings, with a significant focus on agents, representing 32% of the roles, and serving infrastructure at 29%. The majority of these positions are within the Engineering function, with hiring concentrated in the United States. Frequent technical tags include model_serving, inference_infra, and agent_orchestration, suggesting a direction toward operationalizing AI models. In the last 30 days, Unity has posted 27 new AI roles, a substantial increase of 440% compared to the previous 30-day period.
Unity currently has 53 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 Data Scientist (3), Senior Machine Learning Infrastructure Engineer (3). Most positions are in Engineering and Research.
Unity's active AI hiring is concentrated in: agents (36%), serving infrastructure (28%), data (19%). 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 (40 roles), Canada (5 roles), Israel (4 roles), China (4 roles).
Job postings at Unity most frequently reference: model serving, inference infra, recommender systems, agent orchestration, llm observability.
In the past 30 days, Unity has posted 13 new AI-related roles. That is a -62% change versus the prior 30 days (34 → 13).
| Title | Stage | AI score |
|---|---|---|
| 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 |
| 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. |
| 7 |