Cantina

Machine Learning Engineer, Video

Cantina

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $175,000 - $225,000 per year

Job Level

JuniorMid-Level

Tech Stack

AWSCloudDockerDynamoDBKubernetesPythonPyTorchSQLTensorflow

About the role

  • Own model deployment end-to-end – take video AI models from research to production, build robust inference endpoints, optimize performance, and ensure models scale.
  • 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.
  • Engineer video data workflows – build scalable preprocessing pipelines using serverless GPU infrastructure (RunPod, etc.) to transform raw video and audio into model-ready formats.
  • Architect cloud-native ML systems – leverage AWS (S3, DynamoDB, Lambda, ECS) and Kubernetes to build resilient, scalable data and inference infrastructure that can handle terabytes of video data.
  • Automate data annotation at scale – build and maintain labeling pipelines using AWS Ground Truth and Mechanical Turk.
  • Collaborate across teams – work closely with research and product teams to align model requirements and user needs.

Requirements

  • 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
  • Languages: Python, SQL
  • Passionate about video AI, multimodal models, or conversational AI