Senior Machine Learning Engineer

About Us:


Position Summary:


What does this include 
 Collaborate closely with data scientists to transform machine learning models from prototypes into production-ready solutions; work with data engineers to create robust data pipelines, ensuring data quality and appropriate feature engineering for model inputs
 Develop and deploy monitoring solutions to track model performance, detect anomalies, and maintain model health; implement metrics to monitor and measure model and strategy impact
 Implement strategies for retraining models in response to data drift and model performance degradation
 Help to establish standards, approaches and implement required tooling and automation to support the full life cycle for model design and development which includes, but is not limited to identifying objectives, sampling, testing/validation, calibration, and monitoring performance
 Contribute to the development of predictive modeling projects using data mining techniques for estimating current and future member engagement, operational performance, or other business outcomes; apply unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies

Requirements:
 4-7 years work experience as a Machine Learning Engineer or similar role.
 Excellent understanding of machine learning frameworks (Keras/Tensorflow/PyTorch etc.) and libraries (scikit-learn, etc.)
 In depth understanding and hands-on in MLOps Infrastructure and tooling, such as Containerization, ML Workflow specification as DAG and management with Scheduling/Orchestration frameworks, ML platform for feature and model store
 Excellent understanding of computer science fundamentals, data structures, and algorithms.
 Familiar with object-oriented design methodology and application development in Python.
 Familiar with big data-related technologies to manage large volumes of complex data (SQL, pyspark).
 Think outside of the box. Willing to have both hard work and have fun.
 Ability to work in a team and highly collaborative
 Working experience in fraud risk is a plus
 Knowledge of Scala language is a plus
 BS, MS, or PhD in Computer Science or related technical discipline (or equivalent).,