Sofar Ocean
Staff Scientist — Marine Acoustics
San Francisco · Staff+
H1B sponsorship available$121k-$171kDetected 15 days ago
AlgorithmsMachine LearningLLMsForecastingExcelElectrical EngineeringHardware DesignSignal ProcessingResearchCommunication
About the role
- We are expanding our sensing and intelligence capabilities into underwater acoustics and looking for an experienced scientist/engineer in ocean acoustics to help shape and advance Sofar's underwater acoustics platform.
Responsibilities
- Develop capabilities to detect, classify, and localize underwater objects using passive and/or active acoustic sensing methods
- Provide an acoustics-centric perspective on sensing system design, deployment strategy, data quality, and performance validation
- Collaborate with Sofar's oceanic and sensing scientists, software engineers, and firmware teams to translate acoustic research into operational products
- Applying: Write your own first draft - we want to hear your voice and understand your real experience.
- Take-home assessments: Complete these on your own unless we've explicitly said otherwise.
- Hybrid work: We're a hands-on team building hardware and software that operates in the real world - so being together matters.
Requirements
- Deep expertise in underwater acoustics
- Strong understanding of marine acoustic propagation, ambient noise, signal processing, and the practical constraints of ocean sensing
- Experience working with real-world acoustic datasets, field deployments, and/or operational sensing systems
- Experience translating scientific research into operational products or customer-facing capabilities
- Enthusiasm and experience in leveraging LLMs to magnify personal impact
- Familiarity with embedded sensing systems, firmware constraints, or edge processing for acoustic applications
- Familiarity with the constraints of autonomous ocean platforms, including limited power, bandwidth, onboard compute, sensor calibration, and long-duration deployments
- Experience developing acoustic sensing systems or algorithms for detection, classification, localization, mapping, or environmental characterization
- Experience applying statistical signal processing, machine learning, or modern AI methods to acoustic detection, classification, or environmental inference
- Excellent communication skills, and you excel working in a cross-functional team
- Ph.D. in acoustics, ocean engineering, electrical engineering, applied physics, oceanography, or a related field, but we will consider highly qualified candidates of any education level with equivalent experience
- Strong reputation within the ocean acoustics community, with experience contributing to research programs, technical partnerships, or externally funded work
- Comfort working in production codebases when necessary to personally deliver changes.
- $121,000 - $171,000
Compensation
- $121,000 - $171,000
- The range listed is what we reasonably expect to pay for this role at the time of this posting.
- We may ultimately pay more or less than the posted range and may be modified in the future.
- Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, experience, and equity package.
Benefits
- Help shape Sofar's underwater acoustics strategy, and support the technical vision for an underwater acoustics platform that supports real-world marine applications.
- Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, experience, and equity package.
Company info
- Represent Sofar externally with customers, research partners, government agencies, and the broader ocean acoustics community
- At Sofar, we use AI tools in our day-to-day work, and we don't expect our hiring process to be any different.
Visa & Work Authorization
- We do sponsor visas and retain an immigration lawyer to support the process.
- While we can't guarantee sponsorship for every role or situation, if we make you an offer, we'll make every reasonable effort to make it work.
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This listing is sourced directly from Sofar Ocean's careers page and normalized into a canonical job model.