Strong understanding of Machine Learning principles, lifecycle, and deployment practices
Experience in designing and building ML pipelines
Knowledge of deploying ML models on AWS Lambda, EKS, or other relevant services
Working knowledge of Apache Airflow for orchestration of data workflows
Proficiency in Python for scripting, automation, and ML model development with Data Scientists
Basic understanding of SQL for querying and data analysis
Cloud and DevOps Experience
Hands-on experience with AWS services, including but not limited to: AWS Glue, Lambda, S3, SQS, SNS Proficient in checking and interpreting CloudWatch logs and setting up alarm.
Infrastructure as Code (IaC) experience using Terraform
Experience with CI/CD pipelines, particularly using GitLab for code and infrastructure deployments
Understanding of cloud cost optimization and budgeting, with the ability to assess cost implications of various AWS services
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full time