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OpusClip is the world's No.1 AI video agent, built for authenticity on social media. We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used OpusClip to enhance their social presence.
Job Responsibility:
AI System Architecture: Design and build scalable, low-latency AI inference microservices
Engineering-First Model Deployment: Collaborate with the team to build production pipelines for Video Understanding and LLMs
High-Standard "Vibe Coding": Ensure all code is modular, type-safe, thoroughly tested, and maintainable
Performance Optimization: Profile and optimize Python/C++ code and model inference layers to minimize GPU costs and user wait time
R&D to Production: Conduct research on cutting-edge LLMs/multimodal models and rapidly refactor experimental code into stable, production-ready features
Requirements:
Bachelor's degree or above in Computer Science or related fields
3+ years of work experience in a Machine Learning Engineer or AI engineer role
Strong System Design Sense: Understanding of distributed systems, API design (REST/gRPC), asynchronous processing (task queues like Celery/Redis), and database interactions
Solid Engineering Fundamentals: Fluent in Python (C++ or JavaScript is a plus)
Ability to write clean, SOLID, and testable code
Proficiency with Docker/Containerization and CI/CD workflows
AI/ML Proficiency: Skilled in designing and building end-to-end LLM applications, including prompt engineering, context orchestration, and multi-step reasoning flows
Proficient in evaluation and optimization of LLM apps, including LLM-as-judge, retrieval workflows, latency/cost tuning, and guardrail design
Experience in one of the below areas: Video Understanding / Computer Vision
LLM Fine-tuning / RAG Systems
Backend Systems for AI (FastAPI, Vector DBs, Microservices)
Enthusiastic, excellent communicator, self-motivated, and possessing a strong sense of ownership
Nice to have:
Full-Stack AI Experience: Experience building an end-to-end product feature—from the prompt engineering layer down to the API deployment and database schema
Inference Optimization: Experience with TensorRT, quantization (AWQ/GPTQ), or FlashAttention to speed up model performance
Vector Database at Scale: Experience managing vector stores (Pinecone, Milvus, Weaviate) in a production environment
Open Source & Community: Experience building APIs/services/open-source tools with ChatGPT/OpenAI APIs
Projects completed or Research papers published in top-tier conferences (ACL, CVPR, NeurIPS, etc.)