Job Details

Staff Software Engineer - Machine Learning Platform (San Francisco)

Replicate makes it easy for software engineers to run and customize machine learning models in the cloud. With a library of thousands of open-source models, you can get started with one line of code—or fine-tune and deploy your own models when you need something custom. We handle the infrastructure, so you can focus on building. Our team comes from places like Docker, GitHub, and NVIDIA, and we're obsessed with making AI as intuitive as deploying a web app. We build in public, ship fast, and care about getting the details right.

The Platform team at Replicate oversees the entire lifecycle of models, from packaging and deployment to serving, scaling, and monitoring. You'll be developing the infrastructure that supports thousands of models and powers millions of predictions daily. This is a chance to build something truly innovative, where each decision you make has a tangible impact and allows your creativity to shine.

What you'll be doing:

1. Designing and building our deployment and model-serving platform.
2. Building technology to operate the latest advancements in the ML and AI space.
3. Designing systems to maximize the utilization and reliability of our Kubernetes clusters and GPUs, including multi-regional traffic shifting and failover capabilities.
4. Owning and optimizing fair and reliable task allocation and queuing across a diverse set of customers with heterogeneous workloads.
5. Working with our Models team to speed up model inference through techniques like caching, weights management, machine configurations, and runtime optimizations in Python and PyTorch.

Technologies you'll be working with:

• Python, Go, and Node.js
• Kubernetes and Terraform
• Redis, Google BigQuery, and PostgreSQL

We're looking for the right person, not just someone who checks boxes, but it's likely you have…

1. Experience building platforms at scale.
2. Worked in complex systems with many moving parts; you have opinions on monoliths vs. services.
3. Designed and implemented developer-friendly APIs to enable scalable and reliable integration.
4. Hands-on experience setting up and operating Kubernetes.
5. A passion for building tools that empower developers.
6. Strong communication and collaboration skills, with the ability to understand customer needs and distill complex topics into clear, actionable insights. We believe that most of programming isn't just about writing code; building a platform requires a collaborative approach.
7. At least 10 years of full-time software engineering experience.

These aren't hard requirements, but we definitely want to talk with you if…

1. You have worked on machine learning platform teams in the past.
2. You have experience working with or on teams that have put ML/AI into production, even though this role does not entail building ML models directly.
3. You have some exposure to serving Generative AI features where GPUs are costly commodities and workloads can take significant time to finish.

You'll be working from our beautiful office in the Mission, San Francisco, at least 3 days a week.

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