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Currently tracking 35 active AI roles, down 46% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $100k–$300k (avg $197k).

Hiring
35 / 35
Momentum (4w)
↓-51 -46%
60 opens last 4w · 111 prior 4w
Salary range · avg $197k
$100k–$300k
USD · disclosed roles only
Tracked since
Jan 20
last role 4w ago
Hiring velocityscroll left for older weeks
1 new role
Jun 17
1 new role
Sep 29
1 new role
Nov 10
1 new role
17
1 new role
24
2 new roles
Dec 1
2 new roles
15
4 new roles
22
3 new roles
29
6 new roles
Jan 5
1 new role
12
1 new role
19
1 new role
26
11 new roles
Feb 2
5 new roles
9
2 new roles
16
2 new roles
23
3 new roles
Mar 2
8 new roles
9
15 new roles
16
8 new roles
23
19 new roles
30
22 new roles
Apr 6
25 new roles
13
16 new roles
20
25 new roles
27
36 new roles
May 4
22 new roles
11
26 new roles
18
27 new roles
25
13 new roles
Jun 1
23 new roles
8
19 new roles
15
5 new roles
22

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.

Auto-generated from active job postings · last refreshed 2026-05-18

Frequently asked questions

  • What AI roles is Unity hiring for?

    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.

  • What stage of AI development does Unity focus on?

    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.

  • Where is Unity hiring AI talent?

    Unity is hiring AI talent in: United States (40 roles), Canada (5 roles), Israel (4 roles), China (4 roles).

  • What technologies does Unity's AI team work with?

    Job postings at Unity most frequently reference: model serving, inference infra, recommender systems, agent orchestration, llm observability.

  • How many AI roles has Unity posted recently?

    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).

Jobs (7)

42 AI · 190 total active
FilteredStageData×CountryUnited States×Clear all
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Active onlyAI only (≥ 7)
Stage
AllData · 10Serve · 15Agent · 19Ship · 9
Function
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AllUnited States · 98Canada · 24United Kingdom · 15Israel · 12China · 11India · 8Japan · 8Denmark · 4Germany · 4South Korea · 3Lithuania · 1Vietnam · 1
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TitleStageFunctionLocationFirst seenAI score
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.
DataEngineeringMountain View, CAApr 237
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.
DataEngineeringMountain View, CAApr 237
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
Engineering
Mountain View, CA
Apr 23
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.
DataEngineeringMountain View, CAApr 237
Staff Software Engineer, Feature Platform
Staff Software Engineer on the Feature Platform team at Unity, responsible for building and operating infrastructure that powers machine learning, experimentation, and optimization for their ads ecosystem. This involves designing and operating systems that transform high-volume event data into production-grade feature datasets for bidding, attribution, and ranking, working at the intersection of distributed systems, platform engineering, and ML infrastructure. The role owns the full software lifecycle of pipeline systems, supporting both offline training and online feature serving.
DataServeEngineeringMountain View, CA7w ago5
Staff Software Engineer, Feature Platform
Staff Software Engineer on the Feature Platform team at Unity, responsible for building and operating infrastructure that powers machine learning, experimentation, and optimization for their ads ecosystem. This involves designing and operating systems that transform high-volume event data into production-grade feature datasets for bidding, attribution, and ranking, working at the intersection of distributed systems, platform engineering, and ML infrastructure. The role owns the full software lifecycle of pipeline systems, supporting both offline training and online feature serving.
DataServeEngineeringMountain View, CA7w ago5
Staff Software Engineer, Feature Platform
Staff Software Engineer on the Feature Platform team at Unity, responsible for building and operating infrastructure that powers machine learning, experimentation, and optimization for the ads ecosystem. This involves designing and operating systems that transform high-volume event data into production-grade feature datasets for bidding, attribution, and ranking, working at the intersection of distributed systems, platform engineering, and ML infrastructure. The role owns the full software lifecycle of pipeline systems, from architecture to reliability and performance, supporting both offline training and online feature serving.
DataServeEngineeringMountain View, CA7w ago5