Roles and Responsibilities:-

• The Machine Learning Engineer designs, develops, troubleshoots, and debugs software programs as part of machine learning model creation and deployment.
• Works on feature engineering to ensure most information going into the model for prediction accuracy.
• Collaborate with internal stakeholders to understand the business strategy.
• Follows machine learning model management and life-cycle best practice.
• This position is a highly technical role with knowledge of Python programing and machine learning libraries such as NumPy, pandas, matplotlib, scikit-lean, TensorFlow, etc.
• This role has a good understanding of advanced data science concepts, predictive analytics, and machine learning algorithms. This role mentors and validates projects for fellow team members.

Desired Candidate Profile :-

• Works with teammates and departments to define business use cases for data analytics and opportunities for machine learning tool application.
• Data collection from various sources for analysis, organization, and data-cleansing for use in machine learning processes.
• Collaborates with data custodians to build new data structures and views to support future growth of machine learning designs.
• Data analysis to produce insights into data.
• This includes applying machine learning tools and visualizations to provide departments and stakeholders with perspective for decision making.
• Data feature creation and selection.
• Using existing and creating new data sets to formulate accurate, clean data.
• Testing features to ensure relevance and value to machine learning models.
• Data model selection through training, testing, and evaluation.
• Using Python tools and libraries for introspective views into model performance.
• Providing feedback on model performance to the team and departments.
• Deployment of models into certification and production environments.
• Running models for scheduled deliverables and ensuring timely delivery of data visualization and outputs. Model evaluation and maintenance. Monitoring of model performance to ensure maximum performance. Performing adjustments to models and code to adjust as needed. Patching and maintenance of team servers and software.
• Hands-on experience involving latest technology stack like Design using micro services, RESTful API, Web Socket, JSON, XML, SQL, NoSQL, Web API ...
• Documentation of machine learning models and associated code.