AI / ML Engineer

Primary responsibility will be to design, develop, and implement machine learning models and algorithms. This involves researching, experimenting, and selecting appropriate models and techniques to solve specific business problems.

Responsible for preparing and pre-processing large datasets for machine learning tasks. This includes data cleaning, normalization, feature extraction, and transformation to ensure the data is suitable for training and testing machine learning models.

Will train machine learning models using appropriate algorithms and frameworks. This involves selecting and optimizing hyperparameters, cross-validating the models, and evaluating their performance using various metrics such as accuracy, precision, recall, and F1-score.

Collaborate with cross-functional teams, including data scientists, software engineers, and stakeholders, to understand business requirements, gather feedback, and iterate on models and solutions. Effective communication and the ability to explain complex concepts to non-technical stakeholders are crucial in this role.

Contribute to small sections of design review sessions, presenting your work and gathering feedback from the engineering manager or team leader.

Deals with real-world datasets, understand data quality issues, and apply appropriate methods to prepare data for machine learning tasks.

Provides feedback to peers during the design and implementation phases while actively seeking guidance from the engineering manager or team leader.

Contribute to stand-up meetings by identifying potential issues early and proposing preliminary solutions.

Prepare comprehensive presentations and reports, occasionally presenting them to stakeholders with supervision and guidance from the engineering manager or team leader, ensuring clarity and effectiveness in communication.

• May be required to interpret and report data findings and maintain or update specific business intelligence tools, databases, dashboards, systems, or methods.