Claypot AI is hiring a Founding Engineer (Machine Learning)

This role focuses more on engineering than on ML side. We're NOT hiring for data scientists, as we don't build, train, or serve our own models. We provide infra for other companies to build, train, and serve their models. When applying, please do highlight your engineering experience!

Streaming technologies are changing the data landscape and every application that produces and consumes data. Yet, most machine learning models, whose performance is tightly coupled with data quality and data freshness, are still in the batch paradigm.

Claypot unifies streaming and batch systems to make it easier and cheaper for companies to do online prediction and continuous evaluation. Our solution can be especially helpful for problems in fast changing environments such as recommender systems, e-commerce, fintech, and logistics.

Claypot AI was founded by Zhenzhong Xu and Chip Huyen. We're well-funded and working with cool companies!

For more discussion on the problem we're tackling, see:

- Machine learning is going real-time

- The Four Innovation Phases of Netflix’s Trillions Scale Real-time Data Infrastructure

- Self-serve feature platforms: architectures and APIs

We're looking for great machine learning engineers and data scientists to be the foundation of our engineering team. We hire remotely anywhere in the world, as long as you can be available 8.30am - 3pm (PT) for synchronous communication. We plan to bring everyone together a few times a year to hang out and eat tasty food when it's safe to travel 🛫

What you'll do:

• Design and develop a tool that you yourself would use to develop models that leverage fresh data, which requires a deep understanding of the ML workflow.
• Iterate on an interface that can work for both data scientists and data engineers. Spoiler: it's very challenging and involves a lot of back and forth discussion.
• Incorporate engineering best practices into our platform.
• Lead our open-source strategy.
• Lay the foundation for and grow a great engineering team.

We're building a platform to help data science teams experiment and deploy ML models that leverage fresh data. We're looking for machine learning engineers who have:

• Extensive experience in deploying or building infra to deploy ML models in production.
• Discipline in writing production-ready code.
• A product mindset. What you build is customer-facing, so empathy with customers' pain points will be very helpful!
• Clear, concise communication. Because our team consists of engineers from multiple areas of expertise, we need everyone to communicate with each other, not shy away from writing design docs, identifying blockers, and requesting help and resources.

What makes Claypot AI special?

• A culture of transparency, collaboration, and ownership
• A very high bar for engineering craftsmanship
• Expertise in both distributed systems and machine learning
• A strong community
• An opportunity to win over a large, growing, yet untapped market for unified stream and batch computation

What will you get?

• Competitive compensation package
• Flexible remote-friendly culture with options for in-person collaboration
• Learn how to build a startup from the ground up
• Public speaking opportunities
• An environment for you to grow into the career you want

You'll stand out if you are:

• Familiar with ML platform components such as feature store, feature engineering, monitoring & observability.
• Familiar with streaming tools such as Kafka, Kinesis, Flink.
• Ready to take ownership and iterate quickly.
• Motivated by learning and growth.

The job descriptions below are to give a sense of the challenges we're working on. As the company grows, you can define the role that you want with us. We believe in creating an environment for people to grow into their full potential and create the most impact for the team, not squeezing people to fit into job descriptions.

If you're interested in joining us but don't find a job description that fits you, reach out still!