"Learning fast is an engineer’s superpower in the AI era."
Viggle AI is a startup backed by top-tier investors such as a16z and TSFV. At the forefront of the GenAI revolution, we specialize in controllable video generation for content creators, offering advanced technology that empowers creators to realize their visions. Our rapidly growing app is loved by creators from Hollywood professionals to TikTokers, boasting over 30 million users and hosting the second-largest Discord community worldwide.
Viggle is building the next generation of AI-powered avatar and video generation. We're hiring a backend engineer to own and evolve our core platform — a Go-based business API serving millions of creators, and a distributed Python GPU pipeline that turns reference images and driving videos into high-quality avatar renders at scale.
Architect and maintain highly scalable, distributed backend systems powering Viggle's global AI video generation platform across web and mobile clients
Design and implement APIs that power video generation, character/asset management, the creator platform, and monetization (subscriptions, IAP, Stripe)
Develop robust processing pipelines for ingesting user-uploaded videos and orchestrating GPU-heavy workloads (encoding, inpainting, rendering) in near real-time
Productionize ML models from research to scale with our ML team, drive the technical vision for reliability, throughput, and cost efficiency across our GPU fleet — fast-fail coordination, resource reservation, credit safety, GPU utilization
3–5 years of professional backend engineering experience
Excellent proficiency in Go OR Python, with a strong ability and willingness to ramp up on the other — we don't expect day-one fluency in both. Our stack is Go (Gin, GORM) for business APIs and Python (FastAPI, asyncio, aiohttp) for GPU workers.
Experience designing and operating distributed systems at scale — worker coordination, queue-based pipelines, resource reservation, fault recovery
Familiarity with message queues and event-driven architectures (Redis, RabbitMQ, Temporal, NATS, Kafka, or similar)
Working knowledge of containerization and orchestration — Docker, Kubernetes, and modern CI/CD practices
Experience operating GPU inference services in production (PyTorch / TensorRT / Triton) — model loading, warmup, CUDA memory management, OOM debugging
Familiarity with video processing toolchains (FFmpeg, OpenCV, fMP4 / HLS streaming, PTS/timestamp handling)
Background in workflow orchestration (Temporal, Airflow) or stream processing
Dynamic startup culture—accelerate your skills and career growth
Attractive equity packages and highly competitive salary
Comprehensive dental coverage
Complimentary lunch, dinner, snacks, and a vibrant, fun office environment
Compensation Range: CA$100K - CA$300K
