Machine Learning Engineer

WHAT YOU'LL DO 

• Design model serving solutions and develop machine learning-based applications. services, and APIs so as to productionise machine learning models. 
• Set and maintain engineering standards while to grow and go far. 
• Partner with the Data Scientists (those who actually build, train and evaluate ML models) to provide an end-to-end solution for machine learning-based projects. 
• Foster the technological evolution of services and improve their end-to-end quality attributes. 
• Be committed to Continuous Integration and Continuous Deployment. 

 Preferred Skills 

• Familiarity with the engineering aspects of some of popular machine learning practices, libraries, and platforms (e.g. MLflow, Kubeflow, Mleap, Michelangelo, Feast, HopsWorks, MetaFlow, Zipline, Databricks, Spark, MLlib, PyTorch, TensorFlow, and Scikit-learn among others). 
• Comfortable dealing with trade-offs project delivery and quality, especially those involving latency, throughput, and transactions. 
• Experience Continuous Integration & Continuous Deployment processes and platforms, software design patterns and APIs. 
• A person that enjoys staying on top of all the best practices and tools of modern software engineering, while being a advocate of code quality and continuous improvement. 
• Someone interested in large-scale systems and passionate about solving complex problems while being open and comfortable with changes in the tech stack the teams use.