VP of Machine Learning & AI Solutions

Summary

Join a leading financial technology company as the Vice President of AI/ML, responsible for overseeing machine learning model design, development, and deployment. Drive scalable solutions for personalized recommendations, fraud detection, and credit risk assessment.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment

Responsibilities

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime
• Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge

Preferred Qualifications

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions
• Proficiency with Python is required, and experience with Golang is a plus
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently
• Experience working with relational databases, data warehouses, and using SQL to explore them
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams