Machine Learning Engineer, Video

A bit about Cantina:

Cantina, founded by Sean Parker, is a new social platform with the most advanced AI character creator. Build, share, and interact with AI bots and your friends directly in the Cantina or across the internet.

Cantina bots are lifelike, social creatures, capable of interacting wherever humans go on the internet. Recreate yourself using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots are a new media type that offer a way for creators to share infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.

If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!

A bit about the role:

We're looking for a Machine Learning Engineer who thrives at the intersection of cutting-edge AI and real-world deployment. You'll be the bridge between our AI research and production systems, building and maintaining the infrastructure that powers our video-first AI products. This is a generalist role where you'll split your time between deploying state-of-the-art models to production and engineering the data pipelines that feed them

As a ML Engineer, you will:

• Own model deployment end-to-end – Take our latest video AI models from research to production. Build robust inference endpoints, optimize performance, and ensure our models scale seamlessly across cloud infrastructure providers like Baseten.

• Build production-grade inference pipelines – Design, deploy, and maintain ML services that handle real-time video processing. Debug complex issues, optimize latency, and ensure 99.9% uptime for our AI-powered features.

• Engineer video data workflows – Build scalable preprocessing pipelines using serverless GPU infrastructure (RunPod, etc.) to transform raw video and audio data into model-ready formats. Handle everything from format conversion to feature extraction at scale.

• Architect cloud-native ML systems – Leverage AWS services (S3, DynamoDB, Lambda, ECS) and Kubernetes clusters to build resilient, scalable data and inference infrastructure. Design systems that can handle terabytes of video data efficiently.

• Automate data annotation at scale – Build and maintain labeling pipelines using AWS Ground Truth and Mechanical Turk.

• Collaborate across teams – Work closely with research teams to understand model requirements and with product teams to ensure AI capabilities align with user needs.

A bit about you:

• 2+ years of ML engineering, data engineering, or relevant experience

• Experience building video/audio data processing pipelines using serverless GPU infrastructure like Runpod or similar providers.

• Familiarity with machine learning and deep learning frameworks (PyTorch, TensorFlow)

• Experience deploying ML models to inference platforms like Baseten or similar providers

• Track record of adapting to new domains and using ML to improve products

• Experience with AWS services (S3, DynamoDB) and containerization tools like Docker and Kubernetes

• Passionate about video AI, multimodal models, or conversational AI
  

Technical Stack You'll Work With:

• Cloud : AWS (S3, DynamoDB, Lambda, ECS), Kubernetes

• ML Infrastructure : Baseten, RunPod, Docker

• Languages : Python, SQL

• Frameworks : PyTorch, Tensorflow

• Data : Video/audio processing, large-scale data pipelines

• Annotation : AWS Ground Truth, Mechanical Turk

Pay Equity:

In compliance with Pay Transparency Laws, the base salary range for this role is between $175,000-$225,000 for those located in the San Francisco Bay Area, New York City and Seattle, WA. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.

Benefits:

• Health Care — 99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.

• Monthly Wellness Stipend — $500/month to use on whatever you’d like!

• Rest and Recharge — 15 PTO days per year, 10 sick days, all Federal holidays, and 2 floating holidays.

• 401(K) — Eligible to participate on day one of employment.

• Parental Leave & Fertility Support

• Competitive Salary & Equity

• Lunch and snacks provided for in-office employees.

• WFH equipment provided for full-time hybrid/remote employees.