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Full-Time

Software Engineer

Full Stack

Confirmed live in the last 24 hours

Kumo

Kumo

51-200 employees

Generates and deploys predictive models using AI

Enterprise Software
AI & Machine Learning

Mid

Mountain View, CA, USA

Hybrid position.

Category
Full-Stack Engineering
Software Engineering
Required Skills
JavaScript
React.js
Requirements
  • BS (preferred MS, Ph.D.) in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience.
  • Experience designing backend APIs, database schemas, and backend microservices to power a sophisticated user-facing product.
  • Experience writing clean JavaScript code including experience with modern frameworks (React) and debugging tools (Chrome Dev Tools, etc.)
  • Knowledge of (and a passion for) current trends and best practices in full-stack architecture, including performance, accessibility, security, and usability.
  • Experience with Test Driven Development
  • 3+ years of industry experience.
Responsibilities
  • As a Software Engineer at Kumo.AI, you will be responsible for shaping the development and success of our product, which is focused on enabling users across the enterprise, regardless of Machine Learning (ML) background, to build and deploy predictions in production.
  • You'll be closely working with leadership and be responsible for defining customer user journeys, driving the product roadmap, collaborating with cross-functional teams, and ensuring the timely delivery of major features and solutions that meet customer needs on a per-release basis.
  • You will be responsible for designing clean and elegant frameworks to help solve large scale problems, writing high quality code and tests and performing code reviews.

Kumo.ai specializes in creating and deploying predictive models that help organizations make accurate forecasts for critical tasks. Their platform uses Graph Neural Networks to analyze raw relational data, which means it can generate predictions without needing extensive manual data preparation. This approach leads to better accuracy and efficiency while also reducing infrastructure costs by eliminating the need for complex data processing systems. Kumo.ai's platform supports the entire Machine Learning lifecycle, from data preparation to model deployment, and is designed to deliver quick returns on investment for various applications, including customer retention and fraud detection. Unlike many competitors, Kumo.ai offers both Software as a Service and Private Cloud options, making it adaptable for businesses of all sizes. The goal of Kumo.ai is to provide reliable predictive insights that enhance decision-making and operational efficiency for its clients.

Company Stage

Series B

Total Funding

$54.5M

Headquarters

Mountain View, California

Founded

2021

Growth & Insights
Headcount

6 month growth

24%

1 year growth

36%

2 year growth

97%
Simplify Jobs

Simplify's Take

What believers are saying

  • The partnership with Snowflake enhances Kumo.ai's scalability and ease of use, making it more attractive to data scientists.
  • The recent $18 million Series B funding led by Sequoia Capital provides financial stability and resources for further innovation.
  • Kumo.ai's SQL-like Predictive Querying Language simplifies model creation, enabling rapid deployment and broader adoption.

What critics are saying

  • The competitive landscape in predictive AI is intense, with major players like Google and OpenAI posing significant threats.
  • Reliance on partnerships, such as with Snowflake, could limit Kumo.ai's flexibility and independence.

What makes Kumo unique

  • Kumo.ai leverages Graph Neural Networks to eliminate the need for manual feature engineering, setting it apart from traditional ML platforms.
  • The platform's end-to-end capabilities, from data preparation to deployment, streamline the entire ML lifecycle, unlike competitors that require multiple tools.
  • Kumo.ai's high availability SLAs and SOC2 compliance offer robust security and reliability, appealing to enterprise clients.

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