Machine Learning Engineer (Generative AI)

TL;DR

Machine Learning Engineer (Generative AI): Develop and deploy post-training pipelines for text-to-image foundation models, focusing on RLHF, RLAIF, and personalization/customization. Focus on advancing generative AI techniques, debugging models, and maintaining high-throughput fine-tune and evaluation pipelines.

Location: On-site in Toronto or New York

Company

hirify.global is a startup building proprietary generative media models and AI-native creative workflows to make world-class design accessible, with a team experienced in diffusion models and backed by top-tier investors.

What you will do

• Develop end-to-end post-training pipelines for text-to-image foundation models.
• Advance research in RLHF, RLAIF, and model personalization/customization.
• Implement and maintain high-throughput fine-tuning and evaluation pipelines.
• Collaborate with engineers and researchers to build generative AI solutions.
• Debug and iteratively improve machine learning model quality and performance.

Requirements

• On-site presence in Toronto or New York.
• 5+ years of experience developing machine learning models using JAX, PyTorch, or TensorFlow.
• Experience implementing ML foundations such as Transformers, VAEs, and denoising diffusion models from scratch.
• Strong track record in machine learning innovation and deep learning expertise.
• End-to-end understanding of generative media applications and excitement for generative AI advancements.

Nice to have

• Familiarity with Kubernetes and Docker.
• Experience with low-level ML optimization, including CUDA kernel programming.

Culture & Benefits

• Competitive compensation and equity reflecting your impact.
• 4 weeks of vacation.
• Comprehensive health, vision, and dental coverage from day one.
• RRSP/401(k) with employer match up to 4%.
• Top-tier tools and technology to support creativity and productivity.
• Toronto HQ perks including daily in-office meals and convenient location.
• Autonomy to explore, experiment, and run large-scale research and experiments.
• Culture of learning, growth, curiosity, and mentorship.