Full-Time
Distributed Systems Engineer
Confirmed live in the last 24 hours
Kumo
51-200 employees
Generates and deploys predictive models using AI
No salary listed
Junior, Mid
Mountain View, CA, USA
- 1+ years industry experience designing, building and supporting generic systems for large scale data analytics and deep learning in production.
- Experience building large scale distributed fault tolerant services.
- Experience building generalizable APIs and domain specific languages.
- Excellent understanding of low level operating systems concepts including multi-threading, memory management, networking and storage, performance and scale.
- Strong CS fundamentals including data structures, algorithms, and distributed systems.
- Systems programming skills including multi-threading, concurrency, etc. Fluency in C++ is preferred.
- Track record of identifying and implementing creative solutions.
- Experience with cloud infrastructure - AWS, Azure or Google Cloud.
- BS in Computer Science; Masters or PhD Preferred.
- Fluency in English.
- Design and implement complex, distributed platforms for storing data, and scaling parallel algorithms for graph learning workloads.
- Design systems that run across multiple warehouses (eg., Snowflake and Databricks) and multiple clouds (AWS, GCP, Azure).
- Develop generic and generalizable APIs and domain specific languages for big data processing and machine learning (deep learning, graph representation learning).
- Masters or PhD Preferred.
Kumo.ai specializes in creating and implementing accurate predictive models for organizations that need reliable forecasts for critical operations. Their platform uses Graph Neural Networks to analyze raw relational data, which removes the need for manual data preparation and enhances prediction accuracy and efficiency. Unlike many competitors, Kumo.ai's platform covers the entire Machine Learning lifecycle, from data preparation to deployment, while also simplifying infrastructure and reducing costs. The company aims to provide a quick return on investment for its clients, which range from small businesses to large enterprises, by offering flexible deployment options such as Software as a Service (SaaS) and Private Cloud. Founded by experts from major tech companies, Kumo.ai has already gained the trust of leading organizations globally.
Company Size
51-200
Company Stage
Series B
Total Funding
$35.5M
Headquarters
Mountain View, California
Founded
2021
Simplify's Take
What believers are saying
- Kumo's $18M Series B funding will expand its platform and market reach.
- Integration with Snowpark Container Services enhances deep learning capabilities within Snowflake Data Cloud.
- Kumo's platform supports both SaaS and Private Cloud models, offering client flexibility.
What critics are saying
- Increased competition from Databricks' Marketplace may divert potential customers.
- The rise of multimodal AI could overshadow Kumo's current offerings.
- Rapid AI advancements by tech giants may set new industry standards Kumo must meet.
What makes Kumo unique
- Kumo.AI uses Graph Neural Networks for predictive modeling, eliminating manual feature engineering.
- The platform offers a SQL-like Predictive Querying Language for rapid AI model creation.
- Kumo.AI integrates with Snowflake's Native App Framework, enhancing model performance and scalability.
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Growth & Insights and Company News
6 month growth
↓ -2%1 year growth
↓ -3%2 year growth
↑ 0%Data scientists can build highly accurate predictive AI models faster with Kumo AISAN FRANCISCO, June 4, 2024 /PRNewswire/ -- Today at Snowflake Data Cloud Summit 2024 , Kumo AI , a leader in predictive AI, announced it has launched Kumo as a Snowflake Native App in Snowflake Marketplace in private preview. Kumo helps data scientists build highly accurate machine learning (ML) models that better predict user and customer behavior by combining graph learning over enterprise data with generative AI models trained on public data. Kumo's Snowflake Native App is available through Snowflake Marketplace, can be paid for with Snowflake Capacity commitment for eligible customers, and is built using the Snowflake Native App Framework, enabling data scientists to develop predictive models faster than ever before."We understand how difficult building high-performing ML models can be. Our partnership with Snowflake simplifies the process and eliminates many of the typical hurdles that data scientists experience," said Vanja Josifovski, co-founder and CEO of Kumo AI. "By coupling Snowflake's well-known scalability, speed, and reliability with Kumo's specialized AI to identify and maximize the signal hidden in Snowflake data, we can produce highly accurate predictive ML models that are based on the entirety of your data including multiple relational tables, text, and images. Joint customers can unlock the full potential of their Snowflake data to fuel data-driven decisions and make granular predictions such as personalized recommendations."Businesses are trying to maximize revenue-impacting KPIs like conversion, cart size, and retention rates using insights uncovered from historic data, but struggle with efficient approaches and significant model improvements
In the cutthroat world of artificial intelligence, tech behemoths are betting big on a new frontier: multimodal AI. As the shine of text-based chatbots dims, companies are gambling that the future belongs to AI assistants capable of seeing, hearing and conversing with users more naturally and intuitively. The battle for AI dominance has taken on a new dimension, with “multimodal” emerging as the latest buzzword. “The usefulness of multimodal AI comes from its ability to simultaneously process and analyze diverse types of data, such as text, images, audio and video,” ComplyControl Chief AI Officer Mikhail Dunaev told PYMNTS
Credit: cono0430, ShutterstockAn open letter signed by a range of big and small tech companies has committed to responsible development of Artificial Intelligence (AI) at a time of increased public focus on the technology. Four of the the most high-profile signatories of the letter are Google, Microsoft, Meta and OpenAI, four of the most influential firms in global AI products – the latter is notable for being the creator of widely used AI platform ChatGPT. Due to continued development, AI has become increasingly utilised for business purposes, such as automation of general day-to-day tasks, risk management, anti-money laundering and fraud prevention
MOUNTAIN VIEW, Calif. , Nov. 16, 2023 /PRNewswire/ -- Kumo.AI , a Sequoia Capital-backed predictive AI company, announced the general availability of its Kumo.AI platform, enabling rapid creation and deployment of state-of-the-art AI models on private enterprise data. AI practitioners can now use Kumo.AI's intuitive SQL-like Predictive Querying Language to build multiple task-specific AI models in a single day. Founded in 2021 by Stanford University Professor (Jure Leskovec) and former Airbnb and LinkedIn executives (Vanja Josifovski, Hema Raghavan), Kumo.AI helps enterprises unlock customer-focused use cases, such as personalization, churn and LTV prediction, fraud detection, and forecasting.Kumo, cutting edge AI that can query the future (PRNewsfoto/Kumo.AI)While generative AI excels at natural language understanding and generation, it lacks the capability to perform more complex, enterprise-specific tasks, such as predicting customer behavior or detecting fraudulent transactions. Kumo.AI is the first platform that bridges this gap by applying deep representation learning, a technology behind the current AI revolution, to enterprise data in data warehouses
Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More. Kumo, a deep learning platform for relational data, announced today at Snowflake Summit 2023 its integration of deep learning capabilities directly into the Snowflake Data Cloud through Snowpark Container Services.Snowflake’s recently introduced Snowpark Container Services expands the functionality of Snowpark. This update allows organizations to run third-party software and full-stack applications within their Snowflake accounts.According to Snowflake, with this integration customers can maximize their data potential by using cutting-edge tools while maintaining data security and eliminating the need for data movement.Moreover, Snowpark Container Services includes GPU support, which gives data science and machine learning teams a way to accelerate development and bridge the gap between model deployment and consistent data security and governance throughout the AI/ML lifecycle.