ML DevOps Engineer

About the Role:

As an ML DevOps Engineer at Perpay, you will play a critical role in refining and managing our real-time machine learning model deployments. You’ll be working closely with both the Data Science and Data Engineering teams to enhance model reliability, scalability, and integration with the Perpay app, collaborating with the Software Engineering team to ensure seamless deployment in production environments.
The primary focus of the role is to optimize and automate the deployment pipeline for real-time machine learning models, ensuring stability, scalability, and integration with our systems. In addition to your work on model deployments, you will also enhance the data infrastructure, leveraging your DevOps expertise to improve the efficiency and quality of data operations.

Why You’ll Love It Here:

• Impactful Work: Your contributions will directly affect the lives of our customers by creating data-driven solutions that support financial inclusivity
• Cutting-Edge Technology: Work with the latest tools and technologies in data 
• Career Growth: Opportunities for professional development and advancement within a rapidly growing company
• Collaborative Culture: Join a supportive team that values diverse perspectives and innovative ideas

Our greatest strength is our people and we’d love for you to be one of them!

Responsibilities:

• Collaborate with the Data Science and Software Engineering teams to design, implement, and maintain real-time machine learning model deployments
• Build and manage CI/CD pipelines using tools like Travis, Docker, and Terraform for automated testing, deployment, and monitoring of ML models
• Automate the creation of Docker images for training pipelines, deployable APIs, and batch prediction models
• Optimize and enhance the data infrastructure in collaboration with the Data Engineering team, focusing on scalability, performance, and security
• Develop monitoring solutions for model performance and data pipelines, ensuring high availability and fault tolerance
• Collaborate with the Software Engineering team to deploy models integrated into the Perpay app and ensure they meet production-level SLAs
• Implement best practices for model versioning, retraining workflows, and deployment governance
• Drive the adoption of cloud-native solutions on AWS (EC2, ECS, ECR, Redshift) to improve the efficiency of model deployment and data operations
• Ensure seamless integration of data science models with the broader data ecosystem at Perpay, including ETL workflows and batch processes
• Serve as the subject matter expert on machine learning infrastructure and operations, providing guidance to the Data Science and Data Engineering teams

What You’ll Bring:

• Bachelor’s degree or higher in a quantitative/technical field (Computer Science, Engineering, Mathematics, Chemistry, or related field)
• 3+ years of experience working with machine learning infrastructure, model deployments, and cloud-based systems
• Strong experience with AWS services (EC2, ECR, ECS, Redshift) and containerization tools like Docker
• Experience building and managing CI/CD pipelines using tools like Travis or Jenkins
• Deep knowledge of DevOps best practices, infrastructure as code (Terraform), and cloud-native deployment
• Proficiency in Python and familiarity with standard ML frameworks (scikit-learn, PyTorch, TensorFlow, PyMC, etc.)
• Familiarity with data engineering principles, particularly around managing batch processing and ETL pipelines
• Strong communication skills to articulate complex technical concepts and collaborate with cross-functional teams
• Experience working in fast-paced environments and managing multiple projects

Hey, we know not everybody checks all the boxes, so if you’re interested, please apply because you could be just what we’re looking for!