Machine Learning Engineer

Key Responsibilities:

• Design and implement cloud solutions build MLOps on cloud. Preferably AWS Cloud.
  
• Build model and data pipelines for Data Scientists and Data Engineers using AWS cloud services.
  
• Assist in data science model review run the code refactoring and optimization containerization deployment versioning and monitoring of its model quality.
  
• Hands on experience with different features of AWS SageMaker including but not limited to SageMaker Studio Jupyter Notebooks Data Wrangler Clarify etc.
  
• Good understanding of the Python ML Libraries. Should be able to prototype and evaluate new libraries and new features available.
  
• Experience in communicating with Data science team Cloud Infrastructure team and developers to collect requirements describe software product features and technical designs.
  
• Ability and willingness to multitask and learn new technologies quickly
  
• Stakeholder management with good Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences
  

Requirements

• Proficiency in Python and AWS data services.
  
• Proficiency in AI/ML model operations
  
• Experience in building components for data scientists and assisting them in all stages of Model development and deployment. Must have experience in AWS SageMaker and AWS SageMaker Studio
  
• Experience with IDE/notebook software (Jupyter Studio VSCode PyCharm etc)
  
• Experience in building data pipeline using on cloud using Cloud technologies (S3 Lakeformation SQS SNS Spark Glue Step Functions Lambda etc)
  
• Good to have experience in Data Visualization tools likeTableau AWS Quicksight
  

Benefits