Software Engineer, Machine Learning
Listed on 2026-01-12
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Software Development
Machine Learning/ ML Engineer, AI Engineer
Staff Software Engineer, Machine Learning
Location:
Alameda, CA (remote available)
Salary: $189,000 – $243,000 annually
Employment type:
Full-time
Saildrone is a company that has sailed more than 2 million nautical miles and accumulated 50,000 days at sea, earning the trust of governments worldwide. Our unmanned surface vehicles (USVs) deliver continuous, real‑time intelligence in the toughest oceans on Earth—giving partners faster awareness, stronger security, and a decisive edge at sea.
The RoleWe are looking for an experienced and results‑driven software engineer to join the Machine Learning team. In this role you will provide technical leadership, shepherd high‑impact projects to completion, mentor colleagues, and drive the expansion of Saildrone’s machine learning model suite that supports autonomy across our increasingly large fleet of USVs.
Responsibilities- 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 advance the autonomy of robots operating in resource‑constrained environments
- Create positive cross‑functional impact by collaborating with perception, data pipeline, frontend, and product teams
- Foster the technical growth of 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 meet strict performance requirements in noisy and diverse environments
- Extensive experience with one or more ML frameworks (e.g., PyTorch, Tensor Flow, Caffe)
- Extensive experience developing ML Ops pipelines that cover the full ML lifecycle
- Experience with one or more cloud computing platforms
- Experience with runtime libraries for ML models, such as TensorRT
- Ability to lead large ML projects and drive them from start to finish
- Experience mentoring senior and junior software engineers
- Proficiency with Linux/Unix environments
- MS or PhD in a related field
- Experience deploying to NVIDIA Jetson/AGX or similar embedded compute platforms
- Experience with sensor fusion
- Experience developing ML models for radar and/or lidar data
- Experience fielding ML models on robots, cars, cell phones or other edge devices
- Experience with oceanographic, maritime, and/or acoustic data
This position is in Alameda, CA. Our waterfront office offers beautiful views of the San Francisco Bay in always‑sunny Alameda.
All employees are required to provide proof of authorization to work in the U.S. within their first 3 days of work.
The Company does not sponsor employees for work visas or permanent resident cards to work in the U.S.; if sponsorship is required, you will not be eligible for this position.
- Paid time off, including vacation, bereavement, jury duty, sick time, and parental leave
- Comprehensive and competitive medical, dental, and vision plans, with an HSA and employer matching
- Company‑sponsored life insurance
- Stock options
- Annual stipend for continued learning and development
- Quarterly company BBQs at our Alameda HQ (bring your friends and family)
- Free Bay Area public transportation via Alameda
TMA with the Bay Pass Clipper Card
Saildrone is an equal‑opportunity employer committed to diversity and inclusion. We prohibit discrimination and harassment on the basis of race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, and local laws.
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