Machine Learning Engineer

Job purpose

ML Engineer role encompasses designing, building, and maintaining machine learning systems and with the role develops, trains, and deploys machine learning models, automating model deployment and management. As part of larger team, develops and integrates ML analytical components in business solutions and analytical models.

ML Engineer Skills include Model Development and Optimization, Programming with coding skills, Mathematics and Statistics, and Data Handling.

Skills requirement

Must Have:

• Relevant work experience in ML projects
• Relevant work experience in technologies and frameworks used in ML, examples are Apache Airflow, sklearn, MLFlow, TensorFlow
• Knowledge of MLOps architecture and practices
• Knowledge of data manipulation and transformation, e.g. SQL
• Experience working in cloud environment, data cloud platforms (e.g. GCP)
• Programming in Python
• Familiar with software engineering practices like versioning, testing, documentation, code review
• Deployment and provisioning automation tools e.g. Docker, Kubernetes, Openshift, CI/CD

Nice to Have:

• Experience with distributed systems and clusters for both batch as well as streaming data (S3/Spark/Kafka/Flink)
• Experience with monitoring and observability (ELK stack)
• Affinity with Advanced Analytics, Data Science, NLP
• Hands-on experience building complex data pipelines e.g. ETL
• System design and architecture
• Programming in a statically typed language, e.g. Scala, Java
• Good understanding of databases including RDBMS, non-SQL and time-series databases
• Experience with working in an agile/scrum way
• Being a committer to Open Source projects is a strong plus