Senior Machine Learning Engineer

Join our team as a Senior Machine Learning Engineer, where you will focus on developing and maintaining machine learning infrastructure and operations. You will design, build, and maintain the infrastructure required for optimal data extraction, transformation, and loading. You will also design, develop, and implement machine learning models for underwriting and other financial service applications. Collaboration with cross-functional teams, performance monitoring, A/B testing, and mentorship of junior engineers will also be key aspects of this role.

• Design, build, and maintain the infrastructure required for optimal extraction, transformation, and loading of data from various sources.
• Design, develop, and implement machine learning models for underwriting and other financial service applications, ensuring they are robust, scalable, and maintainable.
• Monitor and evaluate the performance of deployed models, ensuring they meet the desired accuracy and efficiency metrics, and implement processes for continuous improvement.
• The ideal candidate will have a strong background in software development, machine learning, and data engineering, with experience in deploying scalable ML models in production environments
• Strong understanding of data structures, algorithms, and software design principles
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch)
• Familiarity with MLOps practices and tools for continuous integration and deployment of ML models
• Analytical Skills: Strong problem-solving skills with the ability to analyze complex data sets, apply advanced data science techniques, and derive actionable insights. Proficient in building predictive models, performing statistical analysis, and utilizing machine learning algorithms to identify trends, patterns, and opportunities for optimization
• Proficiency in programming languages such as Python or Ruby
• Experience with cloud services (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes)
• Educational Background: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree preferred
• Experience: Minimum of 3 years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders