Staff Software Engineer, Machine Learning

Saildrone is hiring a Staff Software Engineer, Machine Learning to design, deploy, and scale machine learning systems supporting autonomy and real-time intelligence across its autonomous surface vehicle fleet. The role leads production ML model development, edge deployment, sensor fusion, ML operations, system optimization, and technical direction.

Responsibilities:

• Production & Mission Impact: Design and deploy production-grade ML models for real-time perception to detect, classify, and track high-value targets. Your work directly enables USVs to operate 24/7/365 in harsh, remote, and hostile maritime environments
• Edge Architecture & Autonomy: Own the full ML lifecycle architecture, ensuring models run reliably on NVIDIA Jetson/AGX platforms. Drive the intelligence that advances autonomous decision-making and behavior for a growing fleet of robotic systems
• Multi-Modal Sensor Fusion: Lead the integration of Saildrone’s unique sensor suite—including cameras, radar, lidar, hydrophones, and bathymetric sensors—to maintain situational awareness in complex, resource-constrained environments
• Dataset & Robustness Engineering: Drive the rapid expansion of proprietary maritime datasets and develop rigorous evaluation frameworks to ensure model performance remains stable across variable sea states and extreme weather
• Strategic ML Ops: Architect and scale cloud-based training pipelines and CI/CD workflows. You will resolve technical ambiguity to ensure the "full stack" from data ingestion to edge deployment is performant and maintainable
• System-Wide Optimization: Lead technical decisions for onboard compute efficiency using runtime libraries like TensorRT, ensuring that rapid model iterations enhance rather than disrupt the overall software stack stability
• Technical Leadership & Vision: Direct large-scale ML projects from concept to completion. Mentor junior and senior engineers while shaping the technical roadmap for the global ML organization. Set engineering standards and influence architectural direction across multiple ML and autonomy teams
• Cross-Functional Integration: Serve as a technical leader across multiple engineering organizations —from Perception to Frontend—to ensure ML-driven insights are actionable for mission pilots and critical to disrupting illegal maritime activity