Machine Learning Engineer

Job Description

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Make creation the world’s favorite entertainment.

About GenTube

Imagination to images in milliseconds. Already 10M+ monthly creations and accelerating. We believe AI creation is the next social medium — as big as video, as habitual as scrolling.

The Opportunity

We’re at the start of a generational shift. Just as YouTube unlocked the world’s videos and TikTok turned short-form into the default entertainment, GenTube is making AI creation the medium of our time. A billion people will move from passive consumption to active creation — and you’ll be one of the engineers building the ML backbone that makes it instant and magical.

The Founders

Josh and Mo scaled platforms to 100M+ users and led a $150M+ AI exit to Microsoft. Now they’re building the defining consumer AI company of the creation era. We’re well-funded with a long runway, and you’re joining the founding team.

The Role

You’ll own the ML systems that power instant, high-quality creation at scale. From sub-second inference pipelines to personalization engines, your work will define how billions experience AI creativity.

What You’ll Do

• Core ML Infrastructure — Build inference pipelines serving millions of generations weekly; design real-time streaming for diffusion, LLMs, multimodal systems; optimize latency across serving, batching, caching, routing.
• Model Performance — Adapt foundation models (SD, Flux, LLMs) for creation; implement quantization, distillation, pruning; experiment with LoRAs, ControlNets, adapters for style and personalization.
• Intelligence Layers — Build ranking, recommendation, and personalization engines; content understanding with embeddings, similarity search, classification; moderation systems that keep outputs safe.
• Production Systems — Scale GPU infra from thousands to millions of daily generations; profile bottlenecks and optimize utilization; implement A/B testing for model variants; monitor drift, quality and latency p99s.
• Relentless Experimentation — Ship new model variants daily; A/B test speed vs. quality; build feedback loops from user behavior to improve outputs.

What We’re Looking For

• ML Engineering Depth — Experience shipping production ML at scale; strong with generative models (diffusion, LLMs, multimodal); PyTorch/JAX fluency; inference serving (Triton, Ray, TorchServe).
• Systems & Infrastructure — Expertise in inference optimization, batching, quantization, model compilation; GPU infra (CUDA, memory management, multi-GPU serving); backend skills in Python/FastAPI, async systems, cloud (AWS/GCP/Azure).
• Product-Focused ML — Care about user experience, not just benchmarks; design for sub-second latency, graceful degradation, and delight.
• Mindset — Startup DNA, fast-moving, scrappy; performance obsessed; quality focused; empathetic to creator intent and expectations.

Bonus

• Built and scaled ML products for consumer apps
• Experience with personalization or recommendation systems
• Open source or side projects showing technical creativity

Why Join

• Be Early — Like YouTube 2005 or TikTok 2018, but for AI creation.
• Own It — our models define latency, quality, and magic for millions.
• Learn From Operators — Founders who’ve scaled ML products to 100M+ users.
• Win Big — Significant equity, competitive comp, asymmetric upside.
• Invent the Future — Solve unsolved inference problems at the AI × consumer edge.

Details

• Location: Toronto — downtown office, high-energy, creative hub
• Compensation: Depending on background, skills and experience
• Benefits: We offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
• Visa: Available support for top candidates

If you want to define the ML infrastructure that makes creation instant, delightful, and accessible to billions — this is your moment. Join us before GenTube becomes the next billion-person creation platform. We encourage you to apply even if you do not believe you meet every single qualification.

We also invite you to apply for related roles and join a growing team focused on ML and software engineering in Toronto.