Principal Scientist — Marine Acoustics

Sofar Ocean is a ocean intelligence company that operates the largest privately-owned ocean sensor network in the world, delivering real-time data and analytics to maritime, government, defense, and research customers. Their two core platforms are Spotter, a global network of solar-powered buoys and sensing devices that measure waves, wind, weather, sound, currents, temperature, water quality, and water level, and Wayfinder, a voyage optimization software that helps shipping operators reduce fuel consumption and emissions by recommending optimal routes, speeds, and schedules based on live maritime weather data and vessel performance models. The company generates over 1.5 million real-time ocean observations per day from more than 2,500 deployed Spotters worldwide, providing ground-truth data trusted by NOAA, the U.S. Navy, and major commercial shipping fleets. Sofar Ocean's mission is centered on building a comprehensive data layer for the ocean to improve safety, efficiency, and environmental stewardship across maritime industries. Their Wayfinder platform delivers an average fuel reduction of 4 to 8 percent per voyage, directly translating into lower greenhouse gas emissions for commercial shipping, one of the world's largest industrial carbon emitters. By combining proprietary sensor infrastructure with advanced weather modeling, Sofar claims forecasts that are 50 percent more accurate than traditional models, enabling better preparation for extreme weather events and protection of maritime assets. What distinguishes Sofar Ocean is its vertically integrated approach: the company owns and operates its own sensor network, runs its own intelligence models, and delivers end-to-end solutions from raw ocean data collection to actionable voyage guidance. This positions them uniquely at the intersection of climate resilience, maritime efficiency, and ocean science, serving a diverse customer base that includes shipping companies, governments, coral reef researchers, and defense agencies seeking live, hyperlocal ocean intelligence at a global scale.

The Role

Sofar designs, builds, and deploys ocean sensing networks at a global scale to power ocean intelligence. We are expanding our sensing and intelligence capabilities into underwater acoustics and looking for a world-class expert in ocean acoustics to set the technical product vision for Sofar’s underwater acoustics platform.

Responsibilities

• Lead Sofar’s underwater acoustics strategy, defining the technical vision for an underwater acoustics platform that supports real-world marine applications.

• Develop capabilities to detect, classify, localize, and track acoustic sources and targets using passive and/or active techniques.

• Drive AI/ML model development for edge-based and cloud-based acoustic intelligence models.

• Advance methods for mapping and characterizing the ocean soundscape—including ambient noise fields, acoustic propagation conditions (e.g., sound-speed structure and transmission loss), and the oceanographic and geoacoustic context that drives them.

• Provide an acoustics-centric perspective on sensing system design—including hydrophone/array selection, calibration, and geometry—as well as deployment strategy, data quality, and performance validation.

• Collaborate with Sofar’s ocean and sensing scientists, hardware and software engineers, to translate acoustics domain expertise into operational products.

• Design and conduct field experiments, at-sea data collection, data analyses, and modeling and simulation studies (including propagation and detection-performance modeling) to evaluate acoustic system performance under realistic ocean conditions.

• Help define product requirements, technical roadmaps, and priorities for new underwater acoustic capabilities.

• Represent Sofar externally with customers, research partners, government agencies, and the broader ocean acoustics community.

Minimum Job Qualifications

• Deep expertise in underwater acoustics

• Practical experience developing acoustic sensing systems or algorithms for detection, classification, localization, mapping, or environmental characterization

• Strong understanding of marine acoustic propagation, ambient noise, signal processing, and the practical constraints of ocean sensing in the real world

• Experience working with real-world acoustic datasets, field deployments, and/or operational sensing systems

• 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

• Experience translating scientific research into operational products or customer-facing capabilities

• 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 leading externally funded research programs or strategic technical partnerships.

• Enthusiasm and experience in leveraging LLMs to magnify personal impact

Bonus Points

• 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.

• Comfort working in production codebases when necessary to personally deliver changes.
  

Estimated Salary Range

• $137,000 - $185,000

• 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.

Our Approach to AI in the Hiring Process:

At Sofar, we use AI tools in our day-to-day work, and we don't expect our hiring process to be any different. Here's how we think about it:

Applying: Write your own first draft — we want to hear your voice and understand your real experience. AI is fine for refining and polishing, not for generating your story.

Take-home assessments: Complete these on your own unless we've explicitly said otherwise. We'll always be upfront about it when AI is allowed.

Interview prep: Go for it. Use AI to research Sofar, practice your responses, and sharpen your thinking before we meet.

During interviews: This is you. We're a small team and we move fast — live conversations are how we get to know you, and we're genuinely curious how you think in real time.

A note on transparency: We're a lean People team, and we use AI to help with things like drafting job descriptions, preparing interview questions, and candidate communications. We don't use it to make hiring decisions — those are always ours.

The through line: use AI to show more of yourself, not less :)

About Working at Sofar:

Hybrid work: We're a hands-on team building hardware and software that operates in the real world — so being together matters. We ask that most team members are in office at least 70% of the time, though some roles (like field technicians or hardware engineering) may require more. Fully remote roles are designated as such in the job posting.

Visa sponsorship: 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.

A note on applying: We mean it when we say we want the strongest people — not the most credentialed ones. If you're excited about this work but don't check every box, please apply anyway. Research consistently shows that underrepresented candidates are more likely to self-select out, and that's a loss for everyone. Sofar operates at the intersection of ocean science, climate, and technology — the problems we're solving are consequential, and the perspectives we bring to them matter. We're actively working to build a team that reflects that.