Job description

THE COMPANY Saildrone is a maritime defense company and the global leader in autonomous unmanned surface vehicles (USVs). With more ocean miles and real-world operational experience than any USV manufacturer or operator, Saildrone maintains active, combat-deployed systems supporting national security and force projection around the world, 24/7/365. Saildrone’s manufacturing and R&D headquarters are located in Alameda, CA, with business development and sales operations in Washington, DC, and deployment hubs in Europe and the Middle East. By combining proven autonomous operations, edge computing, advanced sensing, renewable power, and the most advanced and robust unmanned surface technology on the planet, Saildrone is shaping how the Navy of the future operates. Join a fast-moving, mission-driven team at the forefront of maritime security and autonomous innovation. THE POSITION Saildrone is seeking a Staff Machine Learning Engineer to join our team. Reporting directly to a Senior Member of the Machine Learning team, you will play a critical role in designing, deploying, and scaling machine learning systems that enable autonomy and real-time intelligence across Saildrone’s global fleet. You will expand Saildrone’s model portfolio and ensure reliable, high-performance inference on edge hardware in complex maritime environments. We are looking for a technical leader who creates clarity from ambiguity, drives end-to-end execution, and takes ownership of production ML systems in mission-critical environments. This role is required to be onsite in Alameda, CA in the Bay Area 3 days per week - this is our hybrid model. This is not a remote position. THE TEAM The Machine Learning team is responsible for developing and deploying models that power perception, autonomy, and intelligence across Saildrone’s autonomous surface vehicles. We focus on building scalable, high-performance ML systems that transform multimodal sensor data into actionable insights, enabling persistent maritime awareness in national security and defense environments. THE 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. THE QUALIFICATIONS BS or MS in Computer Science, Electrical Engineering, or a related technical field, as required for the design of complex autonomous systems. 10+ years of experience in Machine Learning or Software Engineering, performing work related to the full ML lifecycle, from cloud-based training to edge deployment. Serve as a technical authority for edge AI systems operating in mission-critical environments. Track record of leading cross-functional technical initiatives in autonomy, robotics, defense, or large-scale distributed systems Demonstrated proficiency in Python, ML frameworks (PyTorch/TensorFlow), and runtime libraries (TensorRT) required to deploy performant computer vision and sensor fusion models. Experience making system-level architecture and modeling decisions under high ambiguity, balancing performance, reliability, and compute constraints in real-world deployed ML systems Track record of communicating technical vision, project roadmaps, and model performance metrics to peers, senior leadership, and cross-functional partners. Ability to work effectively in remote or hybrid environments, including supporting a fleet that operates 24/7/365 in harsh and hostile maritime conditions. Working knowledge of CI/CD best practices, Linux/Unix environments, and MLOps pipelines relevant to maintaining production-grade software at scale. Demonstrated experience mentoring senior and junior engineers and leading end-to-end technical projects from initial concept to mission-ready fielding. The base salary range for this position is shown below. Actual compensation may vary based on skills, experience, and qualifications. This range reflects the base salary for candidates in states requiring pay transparency disclosure. Salary Range $215,000 — $270,000 USD To view Saildrone's candidate privacy policy, please visit: saildrone.com . BENEFITS At Saildrone, we’re building operational capability that matters—and that requires people who can do their best work over the long term. We invest in our team’s well-being, financial security, and professional growth so you can focus on delivering real-world impact with confidence and stability. Our comprehensive benefits package is designed to support you and your family while you contribute to a mission with lasting significance. Generous Time Off: Competitive Paid Time Off (PTO) accrual plus a robust annual holiday schedule and paid sick leave ensure you can rest, reset, and sustain performance over time. Comprehensive Health Coverage: Premium, multi-tier Medical, Dental, and Vision plans with significant company contributions for employees and dependents—providing security and peace of mind. Shared Ownership in the Mission: Equity grants are a core part of our compensation, allowing you to participate in the long-term value you help create through meaningful, operational work. Retirement Savings: Access to a 401(k) retirement plan with flexible pre-tax and Roth payroll contribution options supports long-term financial planning. Investment in Your Growth: We support your continuous learning through an annual professional development reimbursement program, empowering you to sharpen your skills and stay ahead of the curve in a rapidly evolving field. Relocation Support: For eligible roles, we offer relocation assistance to help bring the world’s best talent to our mission-critical locations. Saildrone is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

Requirements

Must-haves

This role is required to be onsite in Alameda, CA in the Bay Area 3 days per week - this is our hybrid model. This is not a remote position.
BS or MS in Computer Science, Electrical Engineering, or a related technical field, as required for the design of complex autonomous systems.
10+ years of experience in Machine Learning or Software Engineering, performing work related to the full ML lifecycle, from cloud-based training to edge deployment.
Serve as a technical authority for edge AI systems operating in mission-critical environments.
Track record of leading cross-functional technical initiatives in autonomy, robotics, defense, or large-scale distributed systems
Demonstrated proficiency in Python, ML frameworks (PyTorch/TensorFlow), and runtime libraries (TensorRT) required to deploy performant computer vision and sensor fusion models.
Experience making system-level architecture and modeling decisions under high ambiguity, balancing performance, reliability, and compute constraints in real-world deployed ML systems
Track record of communicating technical vision, project roadmaps, and model performance metrics to peers, senior leadership, and cross-functional partners.
Ability to work effectively in remote or hybrid environments, including supporting a fleet that operates 24/7/365 in harsh and hostile maritime conditions.
Working knowledge of CI/CD best practices, Linux/Unix environments, and MLOps pipelines relevant to maintaining production-grade software at scale.
Demonstrated experience mentoring senior and junior engineers and leading end-to-end technical projects from initial concept to mission-ready fielding.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningmlci/cdaipythonrest

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Paid Time Off

Professional Development