Machine Learning Engineer

December 14, 2024

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FXC Intelligence

FXC Intelligence is an innovative company that specializes in global payments and financial data intelligence. It provides market-leading data, reports, and insights that are critical to financial institutions and other prestigious organizations, including NGOs like the World Bank. FXC Intelligence helps its clients by providing integral and accurate financial data that redefine industry standards in the financial sector. The company's services are unique in the market, contributing to its rapid growth and strong reputation among some of the world's largest technology companies and financial organizations. FXC Intelligence is committed to promoting a flexible work environment and offering extensive career development opportunities to its team members.

international money transfers β€’ money transfer research and analytics β€’ international payments intelligence β€’ predictive analytics β€’ benchmarking

πŸ“‹ Description

β€’ Building and maintaining our data infrastructure using DevOps and Data Engineering practices, prioritising the needs of stakeholders β€’ Collaborate with Data Practitioners across the company to gain an understanding of their pains and needs and support them where engineering or data science experience is required β€’ Help Data Scientists and ML Engineers write reliable code and ship it to clients β€’ Help Data Analysts and other people in the business by providing the necessary tools and processes β€’ Collaborate with the DevOps team regarding standards and best practices for working with infrastructure in the company β€’ Participate in the migration from on-prem to AWS in the area of data infrastructure β€’ Collaborate with the evolution of the data stack, focusing on scalability, reliability and transparency

🎯 Requirements

β€’ Experience with deploying, testing and monitoring ML models β€’ Experience with data orchestration/pipelines and data warehousing β€’ Good working knowledge of Python and data science libraries β€’ Operational familiarity with ML Infrastructure tools such as Kubeflow, MLFlow and neptune.ai β€’ An understanding of continuous integration and continuous deployment practices, as well as experience with tooling like GitHub actions and Gitlab CI

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