Lead / Senior Machine Learning (ML) Engineer

ML Engineer

About Cloudside

Cloudside is a Cloud and Data consulting company that has deep expertise in Google Cloud Platform, Amazon Web Services, and Microsoft Azure. We help our customers solve complex problems in Infrastructure, DevOps, Application modernization, and Data Management and Analytics.

Our mission is to be the trusted team of Cloud and Data problem solvers, helping our customers achieve the best business outcomes using Cloud as a catalyst. We bring decades of experience and skill in Cloud, Data, and Application Engineering acquired helping customers of all shapes and sizes, and make it available for every customer that we work with.

About The Role

As a Machine Learning Engineer you are responsible for identifying complex problems and developing and deploying novel prototypes and algorithms to solve them. Improves accuracy and functionality of algorithms and understands the overall implications of the entire machine learning frameworks. Translates application requirements into problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to solve problems and discover new products. Integrates knowledge of business and functional priorities. Acts as a key contributor in a complex and crucial environment.

Skill Required

• Object oriented programming with Python
• Scaling the code for an existing model
• Deploying the scaled model into production
• Identify model drifting and how to retrain a drifted model in production
• Creating CI / CD pipelines to automatically deploy the trained / retrained models into production
• Data processing, data design and modelling, deploying the model
• Proficiency with a deep learning framework such as TensorFlow or Keras
• Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
• Experience with solving different flavours of ML problems which includes Computer vision, regression, predictions etc
• Working in public cloud providers (like GCP, AWS)
• Ability to work independently on tasks and deliver with a high-level of quality
• Ability to work in teams and be open to comments and feedback
• Ability to learn quickly and to adapt to a fast-paced environment

Great to Have

Skills : proficiency with a deep learning framework such as tensorflow or keras,creating ci / cd pipelines to automatically deploy the trained / retrained models into production,identify model drifting and how to retrain a drifted model in production,experience with solving different flavours of ml problems which includes computer vision, regression, predictions etc,keras,gcp,working in public cloud providers (like gcp, aws),scaling the code for an existing model,proficiency with python and basic libraries for machine learning such as scikit-learn and pandas,tensorflow,deploying the scaled model into production,python,ability to learn quickly and to adapt to a fast-paced environment,ability to work independently on tasks and deliver with a high-level of quality,data processing, data design and modelling, deploying the model,aws,object oriented programming with python,ability to work in teams and be open to comments and feedback

Skills Required

Identify model drifting and how to retrain a drifted model in production, Proficiency with a deep learning framework such as TensorFlow or Keras, Deploying the scaled model into production, Creating CI CD pipelines to automatically deploy the trained retrained models into production, Scaling the code for an existing model, Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas, Object oriented programming with Python