Reddit is seeking a Staff Machine Learning Engineer for the Ads Creative Effectiveness team to build GenAI-powered ad creative generation pipelines for images, videos, and copy that respect brand guidelines and safety constraints. You will architect end-to-end generative workflows that go beyond basic prompting, enabling asset preservation for logos, fonts, and other brand elements using techniques such as IP-Adapters and LoRAs. You will develop end-to-end image and video editing capabilities (smart-crop, inpaint, outpaint, resize, style-transfer) while maintaining strict brand standards. You will fine-tune large vision-language models to understand winning ad aesthetics and create feedback loops where ad performance metrics (CTR, CVR) influence generation (RLHF/RLPF for Ads). You will engineer robust safety and compliance layers to ensure models do not generate non-compliant, unsafe, or copyright-infringing content. You will partner with Product, Sales, Policy, UX, and other Ads ML teams to integrate ACE capabilities into the Ad Manager UI and the ad delivery path. You will embed guardrails and brand-safety filters, copyright checks, and human-in-the-loop escalation paths to protect users and advertisers. What we’re looking for: Deep ML Expertise with hands-on experience in tree models, neural nets, ranking, and especially LLM/VLM fine-tuning and RLHF/RLPF for ads. Strong experimentation chops with uplift metrics, variance, and minimum detectable effects in generative systems. Ads/Marketplace insight to understand auction dynamics and advertiser pain points. Startup mindse

Reddit is seeking a Staff Machine Learning Engineer for the Ads Creative Effectiveness team to build GenAI-powered ad creative generation pipelines for images, videos, and copy that respect brand guidelines and safety constraints. You will architect end-to-end generative workflows that go beyond basic prompting, enabling asset preservation for logos, fonts, and other brand elements using techniques such as IP-Adapters and LoRAs. You will develop end-to-end image and video editing capabilities (smart-crop, inpaint, outpaint, resize, style-transfer) while maintaining strict brand standards. You will fine-tune large vision-language models to understand winning ad aesthetics and create feedback loops where ad performance metrics (CTR, CVR) influence generation (RLHF/RLPF for Ads). You will engineer robust safety and compliance layers to ensure models do not generate non-compliant, unsafe, or copyright-infringing content. You will partner with Product, Sales, Policy, UX, and other Ads ML teams to integrate ACE capabilities into the Ad Manager UI and the ad delivery path. You will embed guardrails and brand-safety filters, copyright checks, and human-in-the-loop escalation paths to protect users and advertisers. What we’re looking for: Deep ML Expertise with hands-on experience in tree models, neural nets, ranking, and especially LLM/VLM fine-tuning and RLHF/RLPF for ads. Strong experimentation chops with uplift metrics, variance, and minimum detectable effects in generative systems. Ads/Marketplace insight to understand auction dynamics and advertiser pain points. Startup mindse