Senior-level expertise in backend services and data engineering using Python
Hands-on experience with cloud infrastructure (Kubernetes/Docker) and data services (GCP, AWS, or Azure)
Proven track record building production data pipelines and backend services with measurable business impact
Experience working in large codebases with focus on refactoring and systematic improvements
Background building scalable data monitoring and observability systems
Thrive in complexity and find satisfaction in simplifying systems
Make software more maintainable, scalable, and extensible
Collaborate effectively while also driving independent projects to completion
Leverage AI-augmented development tools to increase productivity
Ideal background as Senior Software Engineer with data-intensive systems experience, Senior Backend Engineer with pipeline development expertise, or Senior ML Engineer with production infrastructure experience
Responsibilities
Automate end-to-end ML operations — Build and maintain pipelines covering data collection, preprocessing, model training, and deployment
Optimize system performance — Monitor, profile, and enhance data processing workflows to reduce latency and improve efficiency
Implement robust monitoring — Set up real-time alerts and anomaly detection for critical data feeds
Scale infrastructure — Leverage distributed computing and parallel processing to handle growing data volumes
Drive architectural improvements — Identify and rebuild systems for better performance, maintainability, and cost efficiency
Design for the future — Build data infrastructure that scales seamlessly with business growth