About the job
Join the Kumo Team
Kumo is building the next generation of AI for structured data. With our Relational Foundation Model (RFM), we help some of the world’s largest companies transform their data into predictions, decisions, and end-to-end automated systems.
Our culture is collaborative, fast-moving, and deeply user-obsessed. We value people who take initiative, learn quickly, communicate clearly, and enjoy solving hard technical + people challenges.
Responsibilities
Support and eventually own technical success for enterprise customers adopting the Kumo platform.
Design and build prototypes, workflows, and models across use cases such as:
Recommendations & personalization
Forecasting & demand planning
Fraud detection & risk modeling
Supply chain & logistics optimization
Banking & financial analytics
CRM/growth marketing & user modeling
Work hands-on with large-scale relational datasets, customer pipelines, and production ML systems.
Guide customers through modeling choices, data structures, evals, trust, interpretability, and rollout plans.
Translate ambiguous customer needs into concrete ML solutions and RFM workflows.
Collaborate closely with Kumo engineering and research teams to improve platform capabilities.
Act as a technical leader and trusted advisor, understanding that deploying ML is as much a people and business challenge as it is a technical one.
Deliver demos, workshops, best practices, and partner with executives, PMs, analysts, and data scientists.
Qualifications
Minimum
Bachelor’s or Master’s in a STEM field (CS, EE, Math, Physics, Stats, etc.).
Strong fundamentals in data science, statistics, or machine learning coursework.
Real-world experience via internships, research, industry work, or substantial project work.
Demonstrated intellectual curiosity and initiative, personal ML/AI projects, open source, research, hackathons, or other hands-on experience.
Strong communication skills; comfortable working with people and navigating technical + non-technical audiences.
Genuine enthusiasm for ML/AI, modern modeling approaches, and applying them to real business problems.
Motivated, self-driven, excited to learn fast, and comfortable in a high-velocity startup environment.
Preferred
Deeper expertise in one or more of:
ML infrastructure / data engineering
Full-stack development for ML apps
LLM orchestration, agent systems, or model tuning
Large-scale distributed systems
Forecasting, recsys, fraud, or other applied ML domains
Familiarity with GNNs, temporal models, or structured reasoning.
Enterprise integrations, data platforms, or productionizing ML