About the Role
The individual will lead the development and optimization of core systems within a large-scale AI/ML infrastructure, focusing on reliability, scalability, and performance across distributed environments.
Responsibilities
- Architect and implement scalable backend systems for machine learning workflows
- Optimize data pipelines to handle high-volume, real-time processing
- Collaborate with data scientists to integrate models into production systems
- Ensure platform reliability under heavy computational loads
- Design APIs for seamless internal and external service integration
- Improve system performance through monitoring and profiling
- Support deployment automation and infrastructure as code
- Maintain security standards across all platform components
- Troubleshoot complex issues in distributed environments
- Contribute to technical documentation and system design reviews
Nice to Have
- Master’s degree in computer science or related discipline
- Experience with large-scale feature stores or ML pipelines
- Background in fraud detection or identity verification systems
- Contributions to open-source machine learning projects
- Familiarity with model monitoring and observability tools
Compensation
Competitive salary with equity and performance bonuses
Work Arrangement
Hybrid remote with office availability in major US cities
Team
Collaborative engineering team focused on AI infrastructure and data systems
About the AI/ML Platform Team
This team builds the foundational technology powering intelligent decisioning systems. Engineers work on low-latency data processing, model serving, and scalable storage solutions to support real-time machine learning applications.
What We Value
Technical excellence, ownership, clear communication, and a drive to solve hard problems at scale.
Available for qualified candidates
