3-Month Contract (Potential for Extension)
Remote
Are you passionate about AI and ready to dive into a thrilling project that blends cutting-edge technology with the vibrant world of entertainment? We’re seeking a skilled AI Engineer to participate in building an AI platform that revolutionizes how we create, curate, and deliver short-form content. You’ll work alongside product, engineering, AI, and machine learning experts to build real-world AI systems that shape the future of entertainment.
Responsibilities:
Design, develop, and deploy AI agents and systems that power engaging, short-form content experiences, automating and enhancing content analysis and generation workflows.
Use advanced AI technologies, including agentic workflows, Graph RAG, ontologies, knowledge graphs, and multi-modal Gen AI models.
Curate datasets that deliver highly accurate and creative outputs tailored to entertainment needs.
Take ownership of large components from concept to production, driving innovation and ensuring integration with content delivery systems.
Work closely with DevOps to implement MLOps pipelines, versioning, and scalable deployment via Docker/Kubernetes.
Collaborate closely with product, data science, engineering, and creative teams to shape the technical vision and bring bold, imaginative ideas to life.
Minimum Qualifications:
Proficiency in Python.
Solid experience with development and deployment tools, including containerization (Docker, Kubernetes) and workflow orchestration (Temporal or similar).
Hands-on experience in applied AI engineering focused on Generative AI multi-modal models.
Advanced experience with RAG, particularly in vectorization and the use of vector stores. Experience with GraphRAG is highly desirable.
Knowledge of graph concepts and experience with graph databases (Neo4j or similar). Understanding and experience with ontologies is a plus.
Experience with agentic workflow tools (Pydentic, LangGraph, or similar).
Strong experience with prompt engineering to unlock the full potential of LLMs.
Preferred Qualifications:
Experience building deep learning models using PyTorch or TensorFlow.
Real-world experience with fine-tuning foundation models.
Experience with MLOps practices and tools, including MLflow or similar.
Understanding and practical experience with StructRAG.
Experience with open-source and commercial video processing and computer vision tools (e.g., OpenCV, PySceneDetect, or Detectron2).
What’s in it for you?
Opportunity to build cutting-edge AI systems powering media intelligence and streaming innovations.
Collaborate with forward-thinking teams solving high-impact, real-world challenges.
Join a high-performance engineering environment where your work directly supports strategic initiatives.
Advance your skills in AI, MLOps, and large-scale deployment systems