H2O.ai

Mountain View
Total Offices: 2
321 Total Employees
Year Founded: 2012

H2O.ai Benefits Overview

Compensation + Benefits

Offers 401(K)

Offers life insurance

Offers disability insurance

Offers company equity

Offers dental insurance

Offers health insurance

Offers Health Savings Account (HSA)

Offers Flexible Spending Account (FSA)

Offers vision insurance

Offers generous parental leave

Work-Life Balance + Wellbeing

Offers company-sponsored outings

Offers generous PTO

Provides paid sick days

Provides paid holidays

Company Culture

Offers a remote work program

Provides free snacks and drinks

Recently posted jobs

2 Hours AgoSaved
Remote
India
Artificial Intelligence • Big Data • Machine Learning • Software • Analytics
Design, build, and deploy end-to-end AI solutions—including predictive models, GenAI/LLM and agentic systems—integrating data preparation, feature engineering, model training, deployment, APIs, and monitoring for enterprise customers. Support implementation, demos, and cross-functional collaboration to deliver production-ready AI on the H2O.ai platform.
2 Hours AgoSaved
In-Office
Melbourne, Victoria, AUS
Artificial Intelligence • Big Data • Machine Learning • Software • Analytics
Design, build, and deploy end-to-end AI solutions using H2O.ai platform, including predictive ML, GenAI/LLM and agentic systems. Work on data preparation, feature engineering, model training, evaluation, deployment, monitoring, backend services/APIs, and customer implementations. Support demos and technical workshops and collaborate with cross-functional teams to deliver production-ready AI features and measurable business outcomes.
2 Hours AgoSaved
In-Office
Sydney, New South Wales, AUS
Artificial Intelligence • Big Data • Machine Learning • Software • Analytics
Partner with stakeholders to design, build, validate, and deploy predictive and generative AI/ML solutions. Perform end-to-end data science work (exploration, feature engineering, modelling, evaluation), translate results into business insights, explore GenAI approaches (LLMs, RAG, agentic workflows), and collaborate with engineering on productionisation and MLOps.