Machine Learning Engineer

  • Sydney, Australia
  • Full Time
  • Customer Success
  • Experienced 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. 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.’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 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

As a Machine Learning Engineer in our Professional Services team, you will work closely with Technical teams on the Customer side and Customer Success, Enterprise Support, and Product Engineering teams on the H2O side.

What You Will Do

  • 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 (realtime/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 Engineering team to further enhance our products for needed features
  • Be the trusted solutions advisor for our customers and partners.
  • Communicate effectively with a diverse audience of internal and external stakeholders consisting of: eaustngineers, 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.

What We Are Looking For

  • Bachelor’s or a higher education degree in Computer Science/Engineering, data science, statistics or related field

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 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

Programming Languages/Frameworks

  • Experience in Python, Java, Bash scripting is a must-have. R, Groovy, Scala 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)

    Data Science skills

  • 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.

Programming Languages/Frameworks

  • Proficient in Python or R for data science. Java, Bash scripting, Scala Go are a plus
  • Experience of distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.
  • Experience in Spark and/or Hadoop ecosystem
  • Understanding of writing/interacting with web APIs, preferably REST/JSON or XML/SOAP
  • Understanding of various databases - Relational, NoSql, document, columnar

How to Stand Out From the Crowd

  • 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.


  • Market Leader in Total Rewards
  • Remote-Friendly Culture
  • Flexible working environment
  • Be part of a world-class team
  • Career Growth 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.


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