Senior Machine Learning Engineer

Our client is seeking a dynamic and experienced Senior Machine Learning Engineer to join a leading team in the payment processing industry. Their team is dedicated to advancing the way the world pays, banks, and invests, and we need innovative minds to help us achieve our mission.

Role Overview

We are seeking a Senior ML Engineer with expertise in building and architecting complex systems on AWS infrastructure. As a technical expert, you will lead the design and implementation of highly available, fault-tolerant systems to support mission-critical applications.

Responsibilities

• Set direction and objectives for the team across project impact, ML system architecture, and best practices.
• Adapt standard machine learning techniques to modern parallel computing environments such as distributed clusters, multicore servers, and GPUs.
• Re-evaluate trade-offs of existing features/ML systems and drive large efforts to reduce technical debt, designing from first principles when appropriate.
• Guide the team to develop scalable machine learning systems while influencing engineering culture and standards.
• Address complex online/production performance and evaluation issues requiring in-depth knowledge of machine learning systems.
• Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models.
• Collect and synthesize requirements to create an effective feature roadmap.
• Code deliverables in tandem with the engineering team.

Minimum Qualifications

• Experience in machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical field.
• Proven track record of developing machine learning models at scale from inception to business impact.
• Proficiency in developing and debugging in C/C++ and Java, or scripting languages such as Python and/or shell scripts.
• Demonstrated technical leadership working with teams, owning projects, and setting technical direction.

Preferred Qualifications

• Master's degree or PhD in Computer Science or a related technical field.
• Exposure to architectural patterns of large-scale software applications.
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.