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Currently tracking 26 active AI roles, up 37% versus the prior 4 weeks. Primary focus: Ship · Engineering. Salary range $191k–$410k (avg $293k).

Hiring
26 / 31
Momentum (4w)
↑+17 +37%
63 opens last 4w · 46 prior 4w
Salary range · avg $293k
$191k–$410k
USD · disclosed roles only
Tracked since
Aug '25
last role yesterday
Hiring velocityscroll left for older weeks
1 new role
Jan 27
1 new role
Feb 3
1 new role
Apr 21
4 new roles
Aug 11
1 new role
Sep 29
2 new roles
Oct 13
1 new role
27
2 new roles
Nov 10
2 new roles
Dec 1
1 new role
8
5 new roles
15
2 new roles
Jan 5
5 new roles
12
2 new roles
26
4 new roles
Feb 9
3 new roles
16
5 new roles
23
4 new roles
Mar 2
6 new roles
9
15 new roles
16
20 new roles
23
9 new roles
30
11 new roles
Apr 6
6 new roles
13
19 new roles
20
5 new roles
27
31 new roles
May 4
8 new roles
11
Reddit

Reddit

Consumer · Social

HQ
San Francisco, US
Founded
2005
Size
2,000+
Funding
Public (RDDT)
Website
reddit.com
Blog
reddit.com
Products
  • Reddit

Jobs (2)

26 AI · 155 total active
FilteredStageData×
Show
Active onlyAI only (≥ 7)
Stage
AllData · 2Post-train · 4Serve · 5Agent · 7Ship · 13
Function
AllEngineering · 31
Sort
AI scoreRecentTitle
TitleStageFunctionLocationFirst seenAI score
Senior Engineering Manager, Unified Embeddings Platform
Senior Engineering Manager to lead the Unified Embeddings Platform team at Reddit. This role will architect, implement, and maintain a platform for foundational ML embeddings using state-of-the-art architectures like GNNs, foundational models, and sequence models. The platform will empower ML engineers and data scientists across Reddit to improve the ML feature software development lifecycle, enabling access, storage, and sharing of embeddings.
DataEngineeringUnited States · RemoteOct '258
Senior Machine Learning Engineer, ML Training Platform
Senior Machine Learning Engineer focused on building and maintaining the ML training platform infrastructure at Reddit. This role involves architecting, implementing, and optimizing systems for large-scale ML workflows, including Kubernetes automation, GPU orchestration, and developer experience for internal ML engineers. The goal is to deliver a self-service ML platform that supports continuous iteration and improvement of ML systems.
DataEngineeringUnited States · RemoteOct '257