Staff Backend Software Engineer, Rodeo

📋 Description

• • As a Staff Backend Software Engineer at Twelve Labs, you will be instrumental in architecting and developing the server-side infrastructure that powers our groundbreaking agentic application layer. This is a unique opportunity to join a lean, high-impact team and take ownership of the critical transition from initial prototype to a robust, production-ready platform. Your contributions will directly shape the future of how users interact with and analyze video content through advanced AI.
• • You will be responsible for designing and building sophisticated backend services tailored for complex video processing workflows. This includes managing the entire lifecycle of video data, from ingestion and transcoding to high-quality 4K export, detailed metadata extraction, and intricate timeline operations. Your work will ensure that our platform can handle the demands of enterprise-grade video workloads efficiently and reliably.
• • A core aspect of this role involves architecting highly scalable, available, and resilient systems. You will leverage cloud-native infrastructure, primarily on AWS and GCP, to ensure our services can grow seamlessly with user demand and data volume. This includes implementing best practices for distributed systems to maintain optimal performance under heavy load.
• • You will be tasked with building and optimizing robust APIs that serve both real-time and asynchronous frontend workflows. This encompasses designing efficient data models, implementing effective streaming data delivery mechanisms, and orchestrating long-running background jobs to provide a fluid user experience.
• • A significant focus will be placed on owning the performance and reliability of our distributed video processing pipelines. You will be challenged to achieve low latency and high throughput, ensuring that video analysis and processing tasks are completed swiftly and accurately, even with massive datasets.
• • Close collaboration with frontend engineers will be essential. You will work hand-in-hand with them on API design, defining data models, and strategizing effective streaming approaches to ensure seamless integration and a cohesive product experience.
• • In the realm of ML Integration, you will play a pivotal role in integrating and running inference on advanced computer vision models. This includes tasks such as intelligent video resizing, scene detection, automatic audio noise cleaning, and in-depth visual analysis, all powered by Twelve Labs' state-of-the-art multimodal foundation models.
• • You will be responsible for deploying and serving these ML models efficiently on cloud-based or cloud-native platforms. This involves evaluating the strategic build-vs-buy decisions for model serving solutions and SaaS alternatives to ensure cost-effectiveness and scalability.
• • A key responsibility is working closely with our research team to productionize model outputs. You will translate cutting-edge research into reliable, scalable backend services that can be deployed and maintained in a production environment.
• • Furthermore, you will build sophisticated pipelines that effectively bridge Twelve Labs’ proprietary foundation models with third-party computer vision models. This integration will empower our intelligent video workflows, enabling new and enhanced functionalities for our users.
• • This role requires a deep understanding of service-oriented architecture, microservices, and distributed systems, ensuring that our backend is not only functional but also maintainable and adaptable.
• • You will leverage your strong proficiency in Python for developing backend services, integrating ML models, and creating essential tooling to support the development and operational teams.
• • Hands-on experience running inference on ML/CV models in a production setting is crucial. This is not about theoretical research but about engineering models into robust, reliable services that deliver consistent results.
• • Experience with cloud-native development on AWS or GCP is a must, including proficiency with containerization technologies like Docker and Kubernetes, as well as an understanding of serverless patterns for efficient resource utilization.
• • You should be comfortable working across the entire technology stack and possess the ability to make pragmatic trade-offs in a fast-paced product development environment, balancing innovation with stability and efficiency.
• • Travel up to 25% to Los Angeles is expected, along with up to 10% annually for conferences, off-site meetings, and other business-related events. Participation in on-site interviews and/or in-person onboarding may also be required.