Full-Time
Software Engineer
Cloud Engineering
Confirmed live in the last 24 hours
Kumo
51-200 employees
Generates and deploys predictive models using AI
Mid
Mountain View, CA, USA
- BS (preferred MS, PhD.) in Computer Science or a related field
- 3+ years of experience writing production code in C++, Python, Go, or similar languages.
- Experience with Infrastructure-as-Code development (e.g., Terraform, CloudFormation, Ansible, Chef, Bash scripting, etc.)
- Experience with B2B SaaS and architecting experience in building a large-scale distributed system at scale
- Experience with productionizing cloud applications, including Docker and Kubernetes
- Experience with CI/CD and advanced packaging, versioning, and deployment strategies
- Hands-on experience with Kubernetes (e.g., EKS, GKS, AKS, or OpenSource) on public clouds (AWS, GCP) at scale
- Build and extend components of the core Kumo Cloud Infrastructure and Kumo infrastructure
- Define a culture of engineering excellence and operational efficiency, especially as it relates to development and productization
- Build and automate CI-CD pipelines, release tooling to support continuous delivery, and true zero-downtime deployments across different cloud providers using the latest cloud-native technologies
- Work on advanced tools developed for the world’s leading cloud-native machine learning engine that uses graph deep learning technology
- Develop the infrastructure microservices for features such as usage tracking, diagnostics, monitoring, and alerting at the cloud scale
- Lead automation efforts to streamline global deployment effort
- Build the Kumo ML Ops platform, which will be able to data drift, track model versions, report on production model performance, alert the team of any anomalous model behavior, and run programmatic A/B tests on production models.
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
6 month growth
↑ 16%1 year growth
↑ 29%2 year growth
↑ 93%
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.