r/mlops is a subreddit with 36k members. The community frequently discusses mlops, ai, ml, data, and model, and the most common flair used is mlops education :snoo_hearteyes:, beginner help😓, tales from the trenches :snoo_shrug:, great answers :snoo_hearteyes:, and tools: oss:doge:.
The landing zone for anything MLOps - beginners and pros welcome. Vendors behave!
Popular Topics in r/mlops
#1
Mlops
127 posts
#2
Ai
85 posts
#3
Ml
33 posts
#4
Data
17 posts
#5
Model
17 posts
#6
Gpu
17 posts
#7
Production
16 posts
#8
Deployment
15 posts
#9
Llm
15 posts
#10
Devops
9 posts
Flair Used in r/mlops
#1
MLOps Education :snoo_hearteyes:
: "MLflow vs Kubeflow: Why do some projects use both?"
22 posts
#2
beginner help😓
: "How are you all actually evaluating LLM/agent systems in prod? LLM-as-judge feels shaky"
16 posts
#3
Tales From the Trenches :snoo_shrug:
: "Interesting shift in “Platform Engineering / MLOps” interviews — lots of Kubernetes operations, very little ML"
13 posts
#4
Great Answers :snoo_hearteyes:
: "Physical AI MLOps Challenges"
7 posts
#5
Tools: OSS:doge:
: "I open sourced MLIS, a local-first reference implementation for durable inference jobs"
7 posts
#6
Freemium :snoo_tableflip:
: "litellm's price map is community maintained so it lags, curious how people deal with it"
6 posts
#7
Tools: paid 💸
: "For industrial video MVPs, the model is rarely the bottleneck - the ingest/streaming layer is"
4 posts
Member Growth in r/mlops
Yearly
+12k members(50.2%)
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Last updated: July 7, 2026