H2O.ai is the leading AI cloud company, on a mission to democratize AI for everyone. Customers use the H2O AI Hybrid Cloud platform to rapidly solve complex business problems and accelerate the discovery of new ideas. H2O.ai is the trusted AI provider to more than 20,000 global organizations, including AT&T, Allergan, Bon Secours Mercy Health, Capital One, Commonwealth Bank of Australia, GlaxoSmithKline, Hitachi, Kaiser Permanente, Procter & Gamble, PayPal, PwC, Reckitt, Unilever and Walgreens, over half of the Fortune 500 and one million data scientists. Goldman Sachs, NVIDIA and Wells Fargo are not only customers and partners, but strategic investors in the company. H2O.ai’s customers have honored the company with a Net Promoter Score (NPS) of 78 — the highest in the industry based on breadth of technology and deep employee expertise.
The world’s top 20 Kaggle Grandmasters (the community of best-in-the-world machine learning practitioners and data scientists) are employees of H2O.ai. A strong AI for Good ethos to make the world a better place and responsible AI drive the company’s purpose.
Please join our movement at www.H2O.ai
We are obsessed with customer satisfaction, which usually comes from successful product installation and configuration on the initial engagement. Therefore, we would like you to understand our products profoundly based on various IT infrastructure experiences and skills listed below for this successful engagement. As a Customer Success Engineer at H2O.ai, you will work closely with technical teams on the customer side and Enterprise Support, Product Engineering, and Sales teams on the H2O side.
This role may be based anywhere in the US.
What You Will Do
- Deliver technical professional services to the customer.
- Include installation, configuration, integration of H2O Machine Learning, model management, and cloud products in various customer environments/landscapes.
- Help customers integrate machine learning models/pipelines (python and mojo scoring pipelines) with customer systems.
- Work closely with H2O Data Scientists in advising and developing end-to-end machine learning solutions (from a data engineering perspective) for the customer requirements.
- Provide/gather customer feedback so that you can work with the H2O.ai Engineering team to further enhance our products.
- Communicate effectively with a diverse audience of internal and external stakeholders, Engineers, business people, partners, executives.
- Translate business cases and requirements into value-based technical solutions through machine learning workflows and systems architecture from data ingestion to model deployment.
What We Are Looking For
Container-based Hybrid Cloud System Engineering Skills
- Excellent understanding of working with containers and container-based orchestration frameworks and leveraging them in the development/deployment process. Kubernetes and Docker knowledge is a must-have. Virtualization knowledge (vagrant, vSphere etc.) or Kubernetes cluster management experience is a plus.
- Excellent understanding of system engineering concepts and hands-on working experience with Linux-based environments (OS fundamentals etc). Ubuntu and CentoOS/RHEL mainly.
- Excellent understanding of the cloud ecosystem i.e. what solutions exist on the 3 major public clouds (AWS, GCP, Azure) and when/how to use those components
- Experience in cloud IaaC SDKs like CloudFormation/DeploymentManager or Terraform
- General understanding of security concepts and capability to investigate and debugs issues related LDAP, SAML, OAuth, OpenID, SSH, TLS, network connectivity, firewalls, etc. that are required in any enterprise-grade service architecture/solution
Customer-facing Work Experience
- Experience of working in a customer-facing environment, providing technical services
- Amicable attitude. Aptitude to independently investigate and find solutions to technical problems; urge to learn/master new technologies. Maker mindset.
Education, Experience, and Language
- Bachelor’s or a higher education degree in Computer Science/Engineering
- Minimum 3 to 5 years of experience with cloud computing, Linux systems administration and/or applications development
- Excellent communication skills (proficient in spoken and written English). Additional languages are a plus.
How To Stand Out From the Crowd
- Experience in Python, Java, Bash scripting is a must-have. Go, R, Groovy, Scala are a plus
- Experience in configuration management tools like Ansible, Chef, etc.
- Experience with writing REST API using microservices frameworks in Python or Java
- Experience using Git or other source control tools a big plus
Data Engineering and Data Science Skills
- Experience building data pipelines, ETL data sets, preferably on ‘Big Data’
- Excellent understanding and experience with big data tools like Hadoop, Spark/Kafka, CDP/CDH
- Excellent knowledge of relational databases and various NoSQL database
- Knowledge of basic statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
- Market Leader in Total Rewards
- Remote-Friendly Culture
- Flexible working environment
- Be part of a world-class team
- Career Growth
H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis.