Accertify is the trusted partner to the world's leading brands. With industry-leading fraud prevention, chargebacks, and account protection offerings, we help our clients grow revenue and protect against loss. When you join Accertify, you become part of the digital solution to enable commerce across the globe. Team Accertify provides a solution merchants trust and a career you can trust.
Accertify is growing, and we are looking to add a Senior Machine Learning Engineer to our global fraud-fighting team
How will you make an impact in this role? The Senior Machine Learning Engineer will focus on managing Accertify’s Machine Learning Operations Machine Learning Operations (MLOps) platform and supporting the model monitoring and reporting framework. This individual will use their software development background and strong analytical skills to help build and enhance Accertify’s industry-leading tools with a focus on interacting with our large datasets.
Key Responsibilities:
Refactor ML models developed by data scientists into production-ready code using the existing MLOps platform
Develop production-ready codebases in Python, following SDLC and MLOps principles, analyzing data using SQL and Spark (Scala/ PySpark), and utilizing overall DS hardware infrastructure expertise to maintain, design, and build fast, scalable, and flexible software solutions.
Write unit tests, integration tests, and load tests to ensure production ML models are performant in terms of functionality and latency
Collaborate with cross-functional teams to optimize data pipelines, model deployment, and monitoring systems
Design, develop, test, deploy, maintain, and improve software for ML workflows in a production environment
Manage intricacies of maintaining and supporting the MLOps infrastructure
Produce maintainable, scalable, and high-quality software solutions following SDLC best practices
Demonstrate subject matter expertise and ownership of your team’s services
Elevate the performance of colleagues through training, mentoring, and promoting best practices
Experiment with technologies and propose solutions to colleagues, including architects, data scientists, and leadership
Qualifications:
Master’s degree in Computer Science, Engineering or equivalent experience with 5+ years of experience OR bachelor’s degree in Computer Science or Engineering, or equivalent experience with 7+ years of experience
5+ years of experience in software engineering and software architecture background in an enterprise setting
