ML Solutions Architect

Companies spend millions of dollars to store terabytes of data in data lakehouses, but only leverage a fraction of it for predictive tasks. This is because traditional machine learning is slow and time consuming, taking months to perform feature engineering, build training pipelines, and achieve acceptable performance.

At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists to train powerful Graph Neural Net models directly on their relational data, with only a few lines of declarative syntax known as Predictive Query Language. The Kumo platform enables users to build models a dozen times faster, and achieve better model accuracy than traditional approaches.

As the lead ML Solutions Architect for EMEA , you will serve as the primary technical liaison for Kumo’s customers and prospects in the EMEA region. Your objective is to discover the technical needs of customers and showcase how Kumo can address them (or explain why you think it won’t). With this information, you will craft and tell a story of how Kumo can deliver value to their organization.

Together with the customer and Account Manager, you will put together a plan to solve the customer’s machine learning problems using Kumo. You will leverage your industry knowledge and data science expertise to help the customer craft the solution architecture and machine learning approach for their use cases, and guide them to achieve technical wins. You will maintain relationships with technical champions, ensuring continued success of existing models as well as expansion to new use cases.

The Value You Will Add:

  • Be a Kumo platform superuser – understand the product in and out and how it should be used to solve customer problems.
  • Lead the technical discovery to understand the alignment between what Kumo offers and prospective customer expectations.
  • Conduct product demos of Kumo solving ML problems in a variety of verticals, including finance/fraud, growth/marketing, personalization/commerce, and forecasting/optimization.
  • Guide the customer to achieve meaningful wins on high-impact ML problems, by leveraging your problem-solving skills, data science knowledge, and industry experience.
  • Be hands-on, to help customers overcome challenges they may encounter in achieving sufficient model performance, or integrating Kumo into their production systems.
  • Lead architecture reviews and security assessments.
  • Maintain meaningful relationships with technical influencers and champions within ML teams, both pre and post-sale.
  • Educate current Kumo users on how to successfully use our product, best practices, etc. so that they increase usage across a larger and larger number of internal workloads.
  • Provide market and customer feedback to the Product and Engineering team to refine feature specifications and the product roadmap.
  • Create broader processes for each customer to go through to ensure we can drive repeatable successes in PoCs.
  • Generate Kumo platform educational materials to disseminate amongst current users or prospects.

Your Foundation:

  • Someone who finds genuine satisfaction in solving customer ML problems and helping them deliver value to the business.
  • 2+ years of relevant professional experience working with external customers in deploying AI/ML/data science solutions in production for customers.
  • Proficiency with ML and data science fundamentals, at the level of a bachelors/graduate program.
  • Persuasive communication – ability to present, speak, demo well to customer stakeholders and convince them to partner with Kumo!
  • Self-starter, motivative, resourceful and persistent: demonstrated ability to structure complex problems, take the initiative, and identify creative solutions to deliver outcomes in the face of obstacles.
  • Knowledge of common data science tools around SQL-based data warehousing (eg. Snowflake, Databricks, DBT), BI tools (eg. Tableau, Looker), workflow orchestration, and ML Ops.
  • Excellent spoken and written English skills.
  • Fluency with scripting in Python.
  • Ability to work effectively across time zones. Teammates will be located from PT to CET time zones. Customers will be in GMT/CET, while occasionally as far as SGT.

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