Melio is a TLV-based Fintech startup (and tech Unicorn!) that enables small businesses in the US to pay their bills in more efficient ways. This improves their finances and frees them up to focus more on managing the businesses they love. With our unique approach to small business payments, we're the fastest-growing payment solution in the United States.

What makes Melio unique?

Well, we've made B2B payments as simple as P2P payment apps like Venmo and Bit. Currently, 42% of business payments in the US are made by check… yikes!

We're looking for a Senior Machine Learning Operations engineer (MLOps) that will join the Data Infrastructure team in defining, building, integrating, and deploying the Machine Learning Operation platform, services, and processes and be part of the big data operation.

The goal of an MLOps Engineer is to bridge the gap between development and production - between data science and engineering. Ultimately - deliver value to customers and stakeholders faster.

 

How You’ll Make An Impact

  • Manage infrastructure and configurations-as-code. Create reusable data pipelines and manage machine learning experiment job specifications as code, so that you can easily rerun and reuse a version of your experiment across environments
  • Enable continuous experimentation and comparison against a baseline model
  • Version control code, data, and experimentation outputs
  • Monitor the incoming data to detect data drift
  • Trigger model retraining and set-up a rollback just in case
  • Examine and communicate clearly the technology and architecture choices we make.
  • Continuously improve ML processes, tools, and standards

 

What we’d love to see

  • B.Sc. in Computer Science or equivalent.
  • Over 4 years of Python / Java / Scala software development, MLOps engineering, or technical architectural experience.
  • Experience in orchestrating Machine Learning solutions in production at scale.
  • Applied background in machine learning platform development, software development, CI/CD, and deployment patterns.
  • Experience in Data and ML Orchestration tools such as MLFlow, Snowflake, BigQuery, SageMaker, TensorBoard, Airflow - Advantage
  • Working with Data version control (DVC) and other data-related tools - Advantage

 

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