Senior ML Engineer

Drafted; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Drafted in San Francisco is seeking an ML engineer to help build core infrastructure for training and running our diffusion-model based systems in production. You will collaborate with engineering and research teams to deliver reliable, scalable ML systems.

The role emphasizes production-grade PyTorch code, multi-node training, and potential work with Triton/CUDA kernels to optimize performance. This is a hands-on, in-person position in SF with a small, driven team.

Qualifications

• Experience writing production serving code for diffusion models.
• Experience writing multi-node training code for diffusion models.
• Bonus: experience with custom Triton or CUDA kernels.

Responsibilities

• Build core infrastructure for training and serving ML models in production.

Skills

Production serving

Multi-node training

Model distillation

Tools

PyTorch

Triton

CUDA kernels

Job description

About Drafted

Drafted is unlocking creativity in the physical world. We're building foundational models and generative pipelines that create floor plans and renderings instantly, so anyone can imagine their dream home. Starting with single-family homes, we plan to verticalize across all dimensions of the pre-construction stack.

Generative architecture is a prime domain for applied research with abundant data, verifiable constraints, and a clear value proposition. Our team of second-time founders, engineers, and designers pairs exceptional product taste with deep technical rigor to turn real-world buildability constraints into an intuitive, creative experience.

Drafted's Values

We're a small team working fully in-person in San Francisco. We value high-ownership builders who want to be a part of a talented, highly motivated team. We're guided by the following values:

• Own the mission. We take agency, act like owners, and see problems through to real outcomes.
• Build in the open. We value direct feedback, fast learning, and growth through honest collaboration.
• Move with care and speed. We iterate quickly while staying deeply respectful of our teammates.
• Seek the why. We challenge assumptions, think from first principles, and never stop asking questions.
• Design for everyone. We believe anyone should be able to design and build a home they love.
• Solve what matters. We embrace hard problems and create new paths forward when none exist.

The Role

As an ML engineer, you'll contribute meaningfully to building core infrastructure for training and running our models in production. Our product blends exceptional product craft with deep technical work, so you'll collaborate closely with both the engineering and research teams.

Example Projects

• Teach our ML model how to generate multi-story outputs
• Lower the cost of inference by distilling our model
• Speed up our data labeling processes with computer assisted labeling

Desired Skillset

• Writing production serving code for diffusion models with PyTorch
• Written multi node training code for diffusion models with PyTorch
• Bonus if you've written and tuned performance with custom Triton / CUDA kernels