Member of Technical Staff - Backend Software Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

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About this role

Member of Technical Staff - Backend Software Engineer Toronto, Ontario, Canada "Learning fast is an engineer's superpower in the AI era." About Us: 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 45 million users and hosting the second-largest Discord community worldwide. What We're Looking For About the Role 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. What You'll Do - 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 What You'll Bring - 3 years

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