Founding Engineer (Machine Learning) at Claypot AI
Remote › 🌐 Worldwide, 100% remote position (Posted Apr 16 2022)
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, real-time analytics, automated CI/CD test suite, and automated model retraining. Our solution can be especially helpful for problems in fast changing environments such as recommender systems, e-commerce, fintech, and logistics.
Claypot 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 and The Four Innovation Phases of Netflix’s Trillions Scale Real-time Data Infrastructure.
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. 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 an ML platform that you yourself would want to use to deploy ML models.
Evaluate ML tasks, models, metrics, techniques, etc. that we should support.
Incorporate ML and data science best practices into our platform.
Lead our open-source strategy.
[Optional] Engage with customers to understand their pain points and turn these insights into actionable items.
Lay the foundation for and grow a great engineering team.
We're building a platform to help data science teams deploy, manage, evaluate, and update ML models in real-time. We're looking for machine learning engineers who care about:
Deploying ML for real-world applications.
Improving the developer experience for data scientists / ML engineers.
Ensuring model quality in production via offline/online model evaluation.
Product mindset. What you build is customer-facing, so empathy with customers' pain points will be very helpful!
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 fast ML delivery
What will you get?
Competitive compensation package
Flexible remote-first 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're:
You've developed and deployed ML models in production.
You've worked with MLOps tooling such as MLflow, SageMaker. We might ask you about your favorite ML tool, and why.
You're familiar with concepts such as model store, feature store, monitoring & observability, data distribution shifts, continual learning, etc.
You're familiar with various ways to deploy ML models (e.g. online/batch prediction).
You should join us if you're:
A learner (we're in a new space so there is a lot for us to learn!)
Excited about machine learning and streaming technologies
Open-minded to different ideas, cultures, and backgrounds
Ready to take ownership and iterate quickly
The job descriptions 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!
Please mention that you found the job at Jobhunt.ai