<aside> <img src="https://prod-files-secure.s3.us-west-2.amazonaws.com/810dbb39-269f-44e9-8b16-3cb576560ac6/c31c9bdb-1d94-4f4e-acfd-510f14dbbe30/Frame_1000001809.png" alt="https://prod-files-secure.s3.us-west-2.amazonaws.com/810dbb39-269f-44e9-8b16-3cb576560ac6/c31c9bdb-1d94-4f4e-acfd-510f14dbbe30/Frame_1000001809.png" width="40px" /> About Cuebric:

We're a paradigm-shifting AI SaaS company, an Industry-Grade AI Creative tool for concepting and background production. Cuebric streamlines the process of dimensionalizing images allowing users to go from Concept To Camera™ in minutes.

Cuebric is born inside a Virtual Production stage. In 2023, it was adopted by several film studios in their endeavor to streamline 2.5D and 2.75D background creations.

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Location: Remote Anywhere

Key Responsibilities:

• Develop Cutting-Edge AI Models: Design, train, and deploy state-of-the-art machine learning models tailored for Cuebric’s filmmaking applications, particularly in generative AI and computer vision.
• Develop Intelligent AI Agents: Build and refine agentic AI workflows that interact dynamically with creators, guiding them through storytelling and creative processes.
• Enhance Multi-Agent Collaboration: Implement multi-agent architectures where AI models collaborate in tasks like image generation, refinement, and contextual storytelling.
• Optimize and Scale: Develop scalable data pipelines, optimize models for real-time performance, and ensure deployment readiness for production environments.
• Conversational AI Integration: Implement context-aware AI assistants that respond dynamically to user input, enhancing storytelling guidance.
• Collaborate Across Teams: Work closely with engineers, artists, and product managers to seamlessly integrate AI-powered features into Cuebric’s platform.
• Deploy ML Models at Scale: Develop robust pipelines for model deployment, monitoring, and optimization in cloud-based environments.
• Validate and Iterate: Conduct A/B tests, performance benchmarks, and rigorous validation against key filmmaking and creative industry metrics.

Qualifications:

• Technical Expertise: Strong programming skills in Python, with deep experience in PyTorch and modern ML frameworks.
• Machine Learning Experience: At least 3 years of hands-on experience in ML, deep learning, or computer vision.
• Academic Foundation: Strong theoretical knowledge in machine learning, computer vision, generative AI, or related fields.
• Cloud & Production Deployment: Familiarity with AWS, Docker, Kubernetes, and deploying ML models in cloud environments.
• Data Handling & Pipelines: Experience with Atlas MongoDB or similar database technologies.
• Software Development Best Practices: Experience with CI/CD pipelines, version control (Git), and scalable ML architectures.
• Communication & Collaboration: Ability to work cross-functionally and effectively communicate complex ML concepts to non-technical stakeholders.