Machine Learning Engineer

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Description

Job Summary ML Engineer in SCB Data Analytics team is a unique combination of Data Engineer, MLOps, and a bit of Full Stack. You will be responsible for many engineering tasks from integrating incredible amount of data in SCB, to developing and maintaining a production grade software solution to leverage the data and deliver values to the bank and its millions of customers. Job Description Productionize models: architectural design, develop, test, deploy the whole software components as microservices, Databricks workflows, ADF pipelines, etc. to serve in high load environments. Work closely with data scientists to track performance, set up model monitoring, automated alerts, and further optimize features/models. You will be working on data pipelines and ETL of thousands of tables. Ingesting data from various sources: Azure Blob, sFTP, Kafka, SQL Server, REST API. Running models and integrate into several destinations: Azure Blob, S3, sFTP, Kafka, Databases, emails, MS teams notifications, etc. Further enhance and maintain our in-house platform for managing and automating Features and Models. This involves full stack site, Databricks, job scheduling tools, helper library, and a lot of problem-solving skills. Qualifications Ideal academic background would be a BSc or MSc degree in computer science, software engineering, or information technology. Proficiency with Spark, SQL, Python or Scala. Experience in Software development life cycles: code, unit tests, git or other SCM, CI/

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