Full-Time

Software Engineer

Developer Tools and Productivity

Confirmed live in the last 24 hours

Kumo

Kumo

51-200 employees

Generates and deploys predictive models

Fintech
AI & Machine Learning

Mid, Senior

Mountain View, CA, USA

Hybrid position requires in-office presence.

Category
Backend Engineering
Full-Stack Engineering
Software Engineering
Required Skills
Chef
Bash
Kubernetes
Microsoft Azure
Python
JavaScript
Java
Docker
AWS
Terraform
Ansible
C/C++
Google Cloud Platform
Requirements
  • BS (preferred MS, PhD.) in Computer Science.
  • Must Have: B2B Saas experience, architecting experience in building a large-scale distributed system at scale.
  • 3+ years of experience writing production code in Java, Javascript, C++, or Python (NO NEW GRADS)
  • Experience with productionizing cloud applications, including Docker and Kubernetes, CI/CD and advanced packaging, versioning, and deployment strategies, containers and serverless architecture, online/offline feature stores, model performance monitoring
  • Familiarity with popular MLOps tooling from cloud vendors like GCP (Vertex AI), AWS (SageMaker) or Azure Machine Learning and MLFlow, Kubeflow, etc.
  • Proficiency with general full-stack application development, such as defining data models, building abstractions for business logic, and developing customer-facing Web Front Ends or public APIs/SDKs for the application.
  • Experience with Infrastructure-as-code development (e.g., Terraform, Cloud Formation, Ansible, Chef, Bash scripting, etc.)
  • Core understanding of data modeling and fundamentals of data engineering (e.g. integrations/connectors, pipelines, ETL/ELT processes)
  • AWS Advanced Networking/ AWS Security/ DevOps / Solution Architect Professional Certifications
  • Working knowledge of OAuth, OIDC, SAML, JWT, and identity and access management
  • Proficiency with asynchronous Python frameworks such as Fast API.
Responsibilities
  • Build and extend components of the core Kumo infrastructure
  • Willingness to respond and be a key participant in our incident management process and develop tools for better Root Cause Analysis and reduction in MTTR (mean time to respond)
  • Build and automate CI-CD pipelines, and release tooling to support continuous delivery and true zero-downtime deployments across different cloud providers using the latest cloud-native technologies.
  • 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.
  • You will work on advanced tools developed for the world’s leading cloud-native machine learning engine that uses graph deep learning technology.

Kumo.ai creates predictive models that help organizations with tasks like customer retention and fraud detection. Their platform uses Graph Neural Networks to analyze raw data, which improves accuracy and reduces the need for manual data preparation. Unlike competitors, Kumo.ai offers a comprehensive solution that covers the entire Machine Learning lifecycle and provides flexible deployment options. The company's goal is to enhance decision-making for clients by delivering reliable and efficient predictive capabilities.

Company Stage

Series B

Total Funding

$35.5M

Headquarters

Mountain View, California

Founded

2021

Growth & Insights
Headcount

6 month growth

20%

1 year growth

34%

2 year growth

79%
Simplify Jobs

Simplify's Take

What believers are saying

  • Kumo's $18M Series B funding supports platform expansion and service enhancement.
  • Integration with Snowflake Marketplace broadens Kumo's reach to Snowflake's user network.
  • GPU support via Snowpark Container Services accelerates model development and ensures security.

What critics are saying

  • Competition from Databricks' Marketplace may divert potential customers from Kumo.
  • Rise of multimodal AI by major players could overshadow Kumo's current offerings.
  • Snowflake's native deep learning solutions might be preferred over Kumo's offerings.

What makes Kumo unique

  • Kumo.AI uses Graph Neural Networks for higher accuracy without manual feature engineering.
  • The platform offers a SQL-like Predictive Querying Language for easy model building.
  • Kumo.AI integrates with Snowflake, enhancing scalability and reliability for predictive models.

Help us improve and share your feedback! Did you find this helpful?