Software Engineer, Kumo
Cloud Engineering
Office located in Mountain View, CA
Predictive AI platform
Open for applications
Predictive AI platform
21-100 employees
Open for applications
Office located in Mountain View, CA
21-100 employees
Company mission
To unleash the full potential of enterprise data by bringing the most powerful graph learning approaches, proven in the research world, to all enterprise data.
Role
Who you are
- 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
Desirable
- Experience with popular MLOps tooling from cloud vendors like GCP (Vertex AI), AWS (SageMaker), or Azure Machine Learning, MLFlow, Kubeflow, etc
- Experience with managing popular Data platforms such as AWS EMR, Snowflake, Databricks, etc
- Experience with industry standard security practices, such as security testing, vulnerability assessments, ISO27001, GRC, and risk under compliance
- Extensive experience with Docker/Containers, Jenkins/Flux/Argo, and Terraform in a Linux environment
- Experience with monitoring tools such as Prometheus, Grafana, etc
- Proficiency in developing customer-facing Web Front Ends or public APIs/SDKs for the application
What the job involves
- The Cloud Infrastructure team is responsible for building, operating, and maintaining this platform
- They are responsible for defining and meeting Platform service level objectives, capacity utilization, cost visibility, security compliance, and more. They are highly critical to the success of the Multi-Cloud Platform
- In this role as a Software Engineer - Cloud Infrastructure
- Build and extend components of the core Kumo Cloud 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
Our take
California-based Kumo offers an AI-powered platform to help businesses tackle predictive problems, with a specific focus on graph neural networks. Founded by several AI executives from companies including Pinterest, Airbnb and LinkedIn, the company certainly has strong foundations to build on.
Kumo can be used for lots of different use cases, including new customer acquisition, customer retention, personalization, abuse detection and financial crime detection. The company has attracted considerable interest from enterprises, largely because these companies spend millions of dollars storing data, and yet are unable to effectively leverage most of it due to the time, effort, and skill required.
Having brought in series B funding in 2022, the company is moving to bring its AI technology to more companies, whilst investing in R&D efforts to expand its platform and services. Lately, developments have included the announcement that Kumo can now run deep learning directly in the Data Cloud with Snowpark Container Services (eliminating data exfiltration and security concerns), as well as the ability to deploy Kumo on Databricks' new Lakehouse Apps without ever leaving the ecosystem.
Steph
Company Specialist at Welcome to the Jungle
Insights
31% employee growth in 12 months
Company
Funding (2 rounds)
Sep 2022
$18m
SERIES B
Apr 2022
$18.5m
SERIES A
Total funding: $36.5m
Company benefits
- Gold Plan Health Insurance
- Flexible Spending Accounts for Health and Dependent Care
- Fully remote and hybrid work as an option
- Dental & Vision Coverage
- Unlimited discretionary time off
- South Bay office, 0.4 miles from Mountain View Caltrain stop
- 401k Plans
- Full-week shutdown at end-of-year
- Family Leave
Company values
- Customer-Centric - We have seen firsthand the incredible effort to implement a single, production-quality predictive model. With Kumo, the team aims to solve this problem and make graph learning easy to use, so any business (and person and user) can leverage the power of graph-based AI in minutes
- Optimistic About Innovation - We are optimistic by nature, and in particular about the massive potential of AI and graph learning. The possibility and promise of GNNs, rendered easy and usable for any enterprise to use, motivates our work
- Better Together - We believe enterprise data is inherently highly connected, and that insight about connectedness powers our AI tech. We also believe that the best teams are highly connected. We are all nodes in the network; we are better together
Company HQ
Old Mountain View, Mountain View, CA
Articles
Leadership
Vanja Josifovski
(CEO)Previously served as CTO for Airbnb and Pinterest. Experience as Technical Lead for Google.
Hema Raghavan
(Head of Engineering)Previously served as Senior Director of Engineering for LinkedIn and as a Scientist for Yahoo!
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