VP of Engineering - Machine Learning & AI (Remote)

Sezzle is a leading financial technology company dedicated to empowering consumers by offering flexible payment options and innovative shopping experiences. Our "buy now, pay later" platform enables millions of customers to make responsible purchases, manage payments, while driving growth for thousands of merchants.
Air Force Academy, CO 80840, USA
Machine Learning
Principal Software Engineer
Remote
9+ years of experience
AI · Finance

Description For VP of Engineering - Machine Learning & AI (Remote)

We are seeking a visionary leader to join our core AI/ML team as the Vice President of AI/ML, responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will lead a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space, ensuring our AI-driven features are robust, efficient, and scalable as we continue to grow.

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.

Minimum Requirements:

  • Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
  • At least 9+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Ideal Skills & Experience:

  • Deep expertise in 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.
  • Proficiency with Python is required, and experience with Golang is a plus.
  • Demonstrated technical leadership in guiding teams and owning end-to-end projects.
  • Experience with relational databases, data warehouses, and SQL.
  • Strong familiarity with AWS cloud services, especially for ML solutions.
  • Knowledge of Kubernetes, Docker, and CI/CD pipelines.
  • Comfortable with monitoring and observability tools for ML models.
  • Solid foundation in data processing and pipeline frameworks.

About You:

  • High standards and continuous improvement mindset.
  • Innovative thinking and willingness to challenge conventions.
  • Action-oriented with a focus on speed and calculated risk-taking.
  • Trustworthy, with the ability to respectfully challenge decisions.
  • Results-driven, focusing on key inputs and delivering quality outcomes.
Last updated a month ago

Responsibilities For VP of Engineering - Machine Learning & AI (Remote)

  • Design, build, and maintain scalable ML infrastructure on AWS
  • Collaborate with product teams to develop MVPs for AI-driven features
  • Develop monitoring and alerting frameworks for ML models
  • Support cross-departmental AI utilization
  • Provide production support for ML models
  • Scale ML architecture to support rapid user growth
  • Mentor and elevate team skills
  • Stay updated with the latest advancements in ML technologies and AWS services

Requirements For VP of Engineering - Machine Learning & AI (Remote)

Python
Kubernetes
  • Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience
  • At least 9+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment
  • Deep expertise in machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields
  • Proficiency with Python
  • Experience with relational databases, data warehouses, and SQL
  • Strong familiarity with AWS cloud services
  • Knowledge of Kubernetes, Docker, and CI/CD pipelines
  • Experience with monitoring and observability tools for ML models
  • Solid foundation in data processing and pipeline frameworks

Interested in this job?

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