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About the Role
As a Senior ML Software Engineer on the Data Science Enablement team, you will be the primary software engineering expert for a product area. You will own the successful launches and ongoing operations of high-profile products in production, focusing on new feature delivery, operational excellence, and enhancements to our shared ML platform. You will collaborate with cross-functional teams to deliver scalable, reliable, and low-latency ML solutions, requiring strong technical expertise and collaboration skills.
Responsibilities
- Design, implement, and deploy new features and enhancements to ML products.
- Provide technical ownership of existing and new production ML products.
- Ensure alignment of technical investments with business goals and engineering best practices.
- Contribute to the evolution of the shared ML platform to drive best practices and shared tooling.
- Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging.
- Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.
- Identify and implement opportunities for process, tooling, and system improvements.
- Oversee pre-release testing and coordinate releases to ensure smooth enablement of new features.
- Provide technical guidance and support to other engineers and data scientists.
- Mentor and coach other engineers, supporting their professional growth.
- Foster a culture of collaboration, continuous improvement, and knowledge sharing.
- Proactively identify and resolve blockers, navigate processes, and independently seek out information to drive solutions.
- Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.
Requirements
- 5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience.
- Proven expertise with ML model deployment, API design, and integration into production environments.
- Strong Python programming and relevant ML/data libraries.
- Experience with containerization, orchestration, and AWS cloud services.
- Experience building and operating CI/CD pipelines.
- Experience with monitoring, troubleshooting, and optimizing production ML systems.
- Experience with pre-release testing and release management.
- Demonstrated ability to work independently, navigate ambiguity, and deliver results.
- Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams.
- Experience with OpenAPI, FastAPI, or similar.
Skills
- Python
- ML model deployment
- API design
- Integration
- Containerization
- Orchestration
- AWS
- CI/CD pipelines
- Monitoring
- Troubleshooting
- Optimization
- Release management
- OpenAPI
- FastAPI
- MLFlow
- Model versioning
- Model storage
- Databricks
- Low-latency databases
- DynamoDB
- Terraform Cloud
- AI-assisted coding
Experience Level
- Senior
About the Company
- Global Payments and Worldpay recently joined forces.
- Worldpay is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients.