Machine Learning Engineer Consultant, H2O.ai

• Bachelor’s or a higher education degree in Computer Science/Engineering, data science, statistics or related field
• Experience building data pipelines, ETL data sets, preferably on ‘Big Data’
• Excellent understanding and experience with big data tools like Hadoop and Spark
• Excellent knowledge 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
• Proficient in Python or R for data science. Java, Bash scripting, Scala Go are a plus
• Experience with writing REST API using microservices frameworks in Python or Java
• Experience with dockerization of services (i.e. creating docker images)
• Understanding of Kubernetes based application development
• Experience of visualizing and presenting (EDA) to stakeholders using H2O Wave (plus), or other standard data visualization libraries in the Python and R stacks or using Tableau/PowerBi
• Experience with post production model monitoring tools like H2O ML Ops (plus) MLFlow etc
• Understanding of using a variety of machine learning techniques (supervised/unsupervised, clustering,
• Decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks/tuning
• Techniques
• Understanding of using advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) for practical applications
• Experience of working in a customer-facing environment, providing technical services
• Excellent communication skills (proficient in spoken and written English). Additional languages are a plus
• Amicable attitude. Aptitude to independently investigate and find solutions to technical problems; urge to learn/master new technologies. Maker mindset

Desirable

• We are seeking a highly skilled and motivated Machine Learning Engineer to join our team in Australia
• The successful candidate will have a strong background in machine learning and software engineering, with experience in developing and deploying machine learning models in real-world applications
• The ideal candidate will have a passion for working with data, a strong understanding of machine learning algorithms and techniques, cloud technology and the ability to communicate complex technical concepts to stakeholders
• This is a 3-month contract position based in Toronto, Ontario
• As a Machine Learning Engineer, you will work closely with technical teams on the customer side and Customer Success, Enterprise Support, and Product Engineering teams on the H2O side
• Deliver technical professional services to the customer
• Working closely with H2O Data Scientists in advising and developing end to end machine learning solutions (from a data engineering perspective) for the customer requirements
• Integrating H2O products with customer data sources for model training
• Integrating machine learning models/pipelines (python and mojo scoring pipelines) with customer systems for scoring (relatime/batch) as well as model monitoring and operations
• Implementing end to end MLdata flow pipelines that help streamline and data science solutions to a business problem
• Implementing AI driven applications using the open source H2O Wave SDK
• Provide/gather customer feedback so that you can work with the H2O.ai Engineering team to further enhance our products for needed features
• Ensure the scalability, reliability, and performance of deployed models by implementing appropriate monitoring, testing, and debugging processes
• Work on GenAI tools - LLMs, Fine tuning engines, RAG, create GenAI Apps
• Be the trusted solutions advisor for our customers and partners
• Communicate effectively with a diverse audience of internal and external stakeholders consisting of: Engineers, business people, partners, executives
• 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