Software Engineer, Kumo
GNN Expert
More information about location
Predictive AI platform
Job no longer available
Predictive AI platform
21-100 employees
Job no longer available
More information about location
21-100 employees
Company mission
To help data teams solve the world's toughest problems.
Role
Who you are
- You want to solve real-world problems and get things done
- Ph.D. in Computer Science or Machine Learning or related technical discipline, or related practical experience
- 3+ years experience in designing ML algorithm solutions
- 2+ graph-based machine learning papers at top venues such as NeurIPS, ICLR, ICML, etc
- Well experienced in Python and its deep learning framework ecosystem, such as PyTorch
Desirable
- Passionate about OSS, including various contributions
- Experience developing large-scale systems
- Ability to diagnose technical problems, debug code, and automate routine tasks
- Analytical approach coupled with solid communication skills and a sense of ownership
What the job involves
- Join us at the heart of the Kumo Graph Neural Network and Relational Deep Learning architecture, where you'll play a pivotal role in shaping and expanding its capabilities
- You'll drive innovative designs that enhance our GNN backbone and integrate cutting-edge temporal learning strategies
- Your work will bridge the gap between foundational models and GNNs, tackling diverse use cases like recommendation systems, customer retention, forecasting, and fraud detection
- Leverage your expertise in machine learning and AI to solve critical challenges, creating scalable and adaptable solutions that push the boundaries of what’s possible
- Get ready to make a significant impact in a dynamic and exciting environment!
Salary benchmarks
Our take
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' Lakehouse Apps without ever leaving the ecosystem.
Steph
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
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 & Co-Founder)Previously served as the CTO for Airbnb and Pinterest. Also worked as a Technical lead at Google.
Hema Raghavan
(Co-Founder)Previously served as a Senior Director of Engineering for LinkedIn and as a Scientist for Yahoo!
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