Software Engineer, Machine Learning

About Us

With more than 2 million nautical miles sailed and 50,000 days at sea, Saildrone has earned the trust of governments worldwide. Our unmanned surface vehicles (USVs) deliver continuous, real-time intelligence in the toughest oceans on Earth—giving our partners faster awareness, stronger security, and a decisive edge at sea.

Our USVs are long-range, extreme-endurance platforms powered by advanced sensors and proprietary AI - they have been designed to operate where no crewed vessel can. They collect critical insights above and below the surface to support border security, law enforcement, naval operations, and undersea infrastructure protection.

Headquartered in Alameda, CA, with offices in Washington, DC, and global deployment hubs, Saildrone operates missions worldwide. Join a fast-moving, mission-driven team at the intersection of AI, autonomy, and defense technology—where data turns into intelligence, and intelligence drives action.

We’re looking for an experienced and results-driven software engineer to join the Machine Learning team. In this role you will provide technical leadership for the machine learning team, including shepherding high-impact projects to completion and mentoring your colleagues along the way. You will drive the expansion of Saildrone’s machine learning model suite that generates insights and enables autonomy across a growing fleet of unmanned surface vehicles.

Your contributions will advance the intelligence onboard every Saildrone, including the ability to detect, classify, track, and identify high-value targets in real time. These advances will directly support operations that disrupt drug smuggling and human trafficking activity, and will function across a fleet that operates 24/7/365 in harsh, remote, and sometimes hostile environments.

You are an individual that can efficiently resolve ambiguity, lead the design of complex real-time systems, and iterate quickly to deliver the right solution to meet customer’s needs. You will leverage your strong modeling skills to guide experiments, interpret evaluation results, and understand how rapid changes to models affects the entire software stack. You will take ownership of the models you release, ensuring that they run reliably and efficiently on edge hardware and are robust to a large variety of environmental conditions.

As a senior member of the team, you will be expected to lead projects that impact the entire software stack and require collaboration across functional teams.

Join us and play a leading role in advancing intelligent, autonomous systems operating at sea.

• Contribute to the technical vision of the Machine Learning team
• Make architectural decisions around cloud-based ML training workflows
• Develop and deploy performant models that leverage Saildrone’s unique sensor suite (e.g., cameras, radar systems, bathymetric sensors, hydrophones)
• Drive the continuous and rapid expansion of proprietary ML datasets
• Lead the design of new machine learning systems that will advance the autonomy of new robotic systems that operate in resource-constrained environments
• Create positive cross-functional impact by collaborating with perception, data pipeline, frontend, and product teams
• Foster the technical growth of your teammates
• Write efficient, well-tested, reliable and maintainable code following CI/CD best-practices

• 8+ years of professional experience in a relevant domain.
• BS or MS in Computer Science, Electrical Engineering, or related field
• Strong proficiency in Python
• Expert-level proficiency in machine learning fundamentals
• Extensive and proven track record of deploying and maintaining computer vision models that have strict performance requirements in a noisy and diverse environment
• Extensive experience with one or more ML frameworks (e.g., PyTorch, Tensor Flow, Caffe)
• Extensive experience developing ML Ops pipelines that touch the full ML lifecycle, including maintaining ML models under continuous development
• Experience with one or more cloud computing platforms
• Experience with runtime libraries for ML models, such as TensorRT
• Ability to be the technical lead on large ML…