Staff Backend Software Engineer, Rodeo

Twelve Labs is pioneering the development of multimodal foundation models for video comprehension. As a Senior Backend Software Engineer, you will build the server-side infrastructure for their new application layer, focusing on scalable backend services and integrating machine learning models.

Responsibilities:

• Design and build backend services for video processing workflows — ingestion, transcoding, 4K export, metadata extraction, and timeline operations
• Architect scalable, high-availability systems to support enterprise-grade video workloads across cloud-native infrastructure (AWS, GCP)
• Build and optimize APIs that power real-time and async frontend workflows, including streaming data delivery and long-running job orchestration
• Own performance and reliability for distributed video processing pipelines with low latency and high throughput requirements
• Collaborate closely with frontend engineers on API design, data models, and streaming strategies
• Integrate and run inference on computer vision models for tasks like video resizing, scene detection, automatic audio noise cleaning, and visual analysis
• Deploy and serve ML models on cloud-based or cloud-native platforms — evaluate build-vs-buy for model serving and SaaS alternatives
• Work with the research team to productionize model outputs into reliable, scalable backend services
• Build pipelines that bridge TwelveLabs’ foundation models with third-party CV models to power intelligent video workflows

Requirements:

• 10+ years building production backend systems with a track record of designing scalable web services and APIs
• Experience with video-specific tools and frameworks (FFmpeg, AWS Media Services, transcoding pipelines)
• Deep experience with service-oriented architecture, microservices, and distributed systems
• Strong proficiency in Python for backend services, model integration, and tooling
• Hands-on experience running inference on ML/CV models in production — not research, but engineering models into reliable services
• Cloud-native development experience (AWS or GCP), including containerization (Docker, Kubernetes) and serverless patterns
• Comfort working across the stack and making pragmatic tradeoffs in a fast-moving product environment
• Advanced API design skills (RESTful, streaming, async patterns)
• Familiarity with model serving platforms (TorchServe, Triton, SageMaker endpoints, or similar)
• Experience with MLOps practices — model deployment, monitoring, versioning
• Background in media, entertainment, or video streaming platforms
• Exposure to CI/CD pipelines and observability tools (Prometheus, Grafana) for production systems
• Experience with AI-powered product features or agentic application architectures