H2O.ai is the leader in Enterprise AI/Machine Learning with a mission to democratize AI for everyone. H2O.ai is transforming the use of AI with its category-creating visionary machine learning platform. More than 25,000 companies use our open-source platform in mission-critical use cases for Finance, Insurance, Healthcare, Retail, Telco, Sales and Marketing. Our commercial DriverlessAI platform builds on this, with a “use AI to do AI" approach to provide an easier, faster and cost-effective way of implementing data science to provide quantifiable value to the business.
H2O.ai partners with leading technology companies such as NVIDIA, IBM, AWS, Intel, Microsoft and Google. To learn more about how H2O.ai is driving AI Transformation, visit www.h2o.ai.
While a Customer Success Engineer’s day-to-day duties and responsibilities are determined by where they work, there are many core tasks associated with the role.
What You Will Do
- Provide technical customer service and expertise
- Lead Issue Tracking
- Recommend Product Improvements
What You Bring
System Engineering Skills
- Excellent understanding of system engineering concepts and good command of working in a Linux-based environment (OS fundamentals etc). Ubuntu and CentoOS/RHEL mainly.
- Excellent understanding of the Cloud ecosystem i.e. what solutions exist on the 3 major clouds (AWS, GCP, Azure) and when/how to use those components
- Excellent understanding of working with containers and container based orchestration frameworks and leveraging them in the development/solutioning process. Docker and Kubernetes knowledge is necessary
- Virtualization knowledge (vagrant etc.) is also a plus.
- Networking knowledge – Understanding of subnets, proxy servers and reverse proxies
- Security knowledge – authentication, protocols
- General understanding of concepts and capability to investigate and debug issues related LDAP, OAuth, OpenID, SSH, TLS, network connectivity, firewalls etc that are required in any enterprise grade service architecture/solution
Data Engineering Skills
- Experience building data pipelines, ETL data sets preferably on ‘big data’
- Excellent understanding and experience with big data tools like Hadoop and Spark
- Excellent understanding of SQL query language and working with relational databases.
- Understanding of various NoSQL database types and their application scenarios
- Experience in Spark/Kafka and Hadoop ecosystem
- Understanding of Data Science and Machine Learning concepts
- Experience in Python, Java, Bash scripting
- Experience of working in a customer facing environment, providing technical services
- Excellent communication skills (verbal and written, English language). Additional languages a plus.
- Amicable attitude. Aptitude to independently investigate and find solutions to technical problems; urge to learn/master new technologies. Maker mindset.
- Some understanding of H2O.ai products like H2O Core, Sparkling Water, Steam and Driverless AI is beneficial