Company Overview
H2O.ai is a visionary and leader in traditional predictive as well as Generative AI space with a mission to democratize AI for everyone. H2O.ai is transforming the use of AI with its category-creating visionary open source machine learning platforms, H2O-3, h2oGPT, LLMStudio and H2O Wave. More than 18,000 companies use H2O.ai’s open-source products in mission-critical use cases for Finance, Insurance, Healthcare, Retail, Telco, Sales and Marketing.
H2O.ai portfolio also consists of market leading closed source flagship products like Driverless AI, Document AI, Enterprise h2oGPTe, LLM Eval, and LLM Data Studio. MLOps provides a robust model deployment and monitoring platform and AppStore provide a way to deploy and consume business facing AI solutions developed in H2O Wave.
All of these products come together in an end to end machine learning platform called H2O AI Cloud (HAIC) which is available as a hosted SaaS solution as well as on-premise/private cloud based deployments. H2O.ai partners with leading technology companies such as NVIDIA, IBM, AWS, Intel, Microsoft Azure and Google Cloud Platform and is proud of its growing customer base which includes Capital One, Progressive Insurance, Comcast, Walgreens and MarketAxes.
For more information and to learn more about how H2O.ai is driving an AI Transformation, visit www.h2o.ai.
Responsibilities and Duties:
As a Senior Solution Engineer in H2O.ai Professional Services team you will work closely with Technical teams on the Customer side and Product Engineering, Enterprise Support and Sales teams on the H2O side.
Your primary responsibilities would be to
● Be the trusted solutions advisor for our customers and partners and deliver technical professional services to the customer.
● Own and deliver services that include installation, configuration and integration of H2O Machine Learning, Model Management, Generative AU and Cloud products in the customer environment/landscape.
● Provide/gather customer feedback so that you can work with the H2O.ai Engineering team to further enhance our products.
● Translate business cases and requirements into value based technical solutions through the architecture of machine learning workflows and systems from data ingestion to model deployment.
● Architect, design, and implement end to end Predictive and Generative AI Machine Learning and Data Science solutions that help customers realize the value of their investments in H2O.ai products and services.
● Communicate effectively with a diverse audience of internal and external stakeholders consisting of: Engineers, business people, partners, executives.
● Present at meetups and webinars in the Data Science community, and be an integral part of the Maker culture of creating the best products and solutions.
Qualifications and Skills:
Education and Experience
● Bachelor’s or a higher education degree in Computer Science/Engineering
● Minimum 6 to 8 years of experience with cloud computing/linux systems and architecting end to end data processing pipelines or data intensive enterprise solutions
System/Cloud Architecture 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 and implementation experience 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 and implementation experience with containers and container based orchestration frameworks and leveraging them in the development/solutioning process. Kubernetes and Docker knowledge must have. Virtualization knowledge (vagrant etc.) is a plus.
● Excellent understanding of distributed systems/services architecture and enterprise grade solutions/software
● Good understanding and implementation/integration experience of LDAP, OAuth, OpenID, SSH, TLS, network connectivity, firewalls etc that are required in any enterprise grade service architecture/solution
Programming Languages/Frameworks
● Experience in Python, Java, Bash scripting is a must have. Go, R, Groovy, Scala are a plus
● Experience in cloud IaaC sdks like CloudFormation/DeploymentManager or Terraform
● Experience in configuration management tools like Ansible, chef etc.
● Experience with writing REST API using micro services frameworks in Python or Java
Data Engineering Skills
● Excellent understanding and experience at building data pipelines and processes supporting data transformation, data structures, metadata, dependency and workload management in ‘big data’ environments.
● Experience of manipulating, processing and extracting value from large disconnected datasets.
● Excellent understanding and experience with big data tools like Hadoop and Spark/Kafka for batch and streaming processing of data.
● Excellent understanding and experience of SQL query language and working with relational databases.
● Experience of NoSQL database types and understanding of their disparate application scenarios
Data Science skills
● Excellent understanding and experience of deploying Large Language Models in a containerized environment
● Knowledge of overall Generative AI landscape and concepts.
● Knowledge of basic statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
Additional Requirements
● 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.
H2O.ai Perks!
● Flexible work hours and time off.
● Opportunity to work closely with some of the best engineering talent and the best data scientists/Kaggle Grandmasters in the world.
H2O.ai is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.
