Early Career - Engineering

Come and change the world of AI with the Kumo team!

Companies spend millions of dollars to store terabytes of data in data lakehouses, but only leverage a fraction of it for predictive tasks. This is because traditional machine learning is slow and time consuming, taking months to perform feature engineering, build training pipelines, and achieve acceptable performance.

At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists to train powerful Graph Neural Net models directly on their relational data, with only a few lines of declarative syntax known as Predictive Query Language. The Kumo platform enables users to build models a dozen times faster, and achieve better model accuracy than traditional approaches.

We’re looking for motivated and talented new grads to join us in the following areas:

Data Engineering

Infrastructure Engineering

Distributed Systems Engineering

You'll have the opportunity to work alongside world-class engineers, researchers, and leaders from top institutions like Stanford.

• Design & Build: Help design the core systems for model training, inference, and scaling, working on everything from system architecture to APIs.
• Innovate: Contribute to the development of cutting-edge machine learning techniques tailored to work seamlessly with large-scale data warehouse systems.
• Collaborate: Work closely with engineering leaders and research scientists to bring new ideas to life and tackle real-world challenges.
• Deliver: Build and deploy production-quality systems that scale, ensuring the system is fast, reliable, and secure.

• Degree: Recent graduate with a BS in Computer Science, Engineering, or a related field. If you have an MS or Ph.D., that’s a bonus!
• Skills: Strong foundation in software development, systems design, and algorithms. Proficiency in programming languages like Python, Java, or C++.
• Passion: A deep interest in machine learning and cloud technologies. You’re excited about building scalable, high-performance systems.
• Curiosity: An eagerness to learn and grow in an innovative, fast-paced environment.

• Experience with cloud platforms like AWS, Azure, or GCP.
• Knowledge of distributed systems and databases.
• Exposure to machine learning frameworks like PyTorch or TensorFlow.
• Hands-on experience building APIs or microservices.
• Contributions to open-source projects, research papers, or university-based ML work.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.