AI Engineering Lead - Scalable ML for Video Apps

OpusClip; Mountain View (CA); On-site; USD 210,000 - 320,000; Full time

Job summary

OpusClip, the world’s No.1 AI video agent, is seeking a hands-on AI Engineering Lead based in Mountain View, CA. You will ship AI/ML models from prototype to production at scale, focusing on post-training optimization, data feedback loops, and inference efficiency for self-hosted deployments.

You will set the technical roadmap, review architecture, mentor engineers, and balance model quality with latency and infrastructure costs while aligning with product goals and video applications.

Qualifications

• Proven experience shipping AI/ML models from prototype to production at scale.
• Deep expertise in model post-training: fine-tuning, preference optimization, evaluation, and learning from user feedback.
• Experience building data flywheels that convert user behavior and feedback into training data for continuous improvement.
• Strong inference optimization experience for self-hosted models: latency, throughput, GPU utilization, quantization, and serving cost.
• Practical experience applying LLMs or multimodal models to video applications such as highlight detection, content curation, ranking, and editing decisions.

Responsibilities

• Set the technical roadmap and architecture for AI initiatives.
• Mentor engineers and manage a small high-performing AI team.
• Balance model quality, latency, reliability, and infrastructure cost in product decisions.
• Collaborate with product and design teams to ship features that improve creator workflows and video enhancements.

Skills

AI/ML deployment

Model evaluation

Inference optimization

Multimodal models

Tools

GPU inference

Self-hosted models

Job description

OpusClip, the world’s No.1 AI video agent, is seeking a hands-on AI Engineering Lead based in Mountain View, CA. You will ship AI/ML models from prototype to production at scale, focusing on post-training optimization, data feedback loops, and inference efficiency for self-hosted deployments.

You will set the technical roadmap, review architecture, mentor engineers, and balance model quality with latency and infrastructure costs while aligning with product goals and video applications.