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Senior ML Engineer - AI Creation Infrastructure

1851 labs Canada
Visa Sponsorship Relocation
This Job is No Longer Active This position is no longer accepting applications
AI Summary

Design and build ML systems for instant, high-quality creation at scale. Adapt foundation models, implement quantization, and optimize latency. Ship new model variants daily and experiment with LoRAs and ControlNets.

Key Highlights
Build inference pipelines serving millions of generations weekly
Adapt foundation models for creation and implement quantization, distillation, pruning
Optimize latency across serving, batching, caching, routing
Ship new model variants daily and A/B test speed vs. quality
Implement A/B testing for model variants and monitor drift, quality, and latency p99s
Technical Skills Required
PyTorch JAX Triton Ray TorchServe CUDA Python FastAPI async systems AWS GCP Azure
Benefits & Perks
Generous health, dental, and vision benefits
Unlimited PTO
Paid parental leave
Relocation support as needed

Job Description


Mission

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. 


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