The Role:
Sofar designs, builds, and deploys ocean sensing networks at a global scale that provide unique observational knowledge of the ocean environment. We are expanding our sensing capabilities into underwater acoustics to detect, classify, and locate underwater objects, and to create an acoustic map of the marine environment. We are looking for an experienced scientist in ocean acoustics to help shape and advance Sofar’s underwater acoustics platform.
Responsibilities:
Help shape Sofar’s acoustics research and development strategy, contributing scientific and technical direction for an underwater acoustics platform that supports real-world marine applications
Develop capabilities to detect, classify, and localize underwater objects using passive and/or active acoustic sensing methods
Advance methods for creating acoustic maps of the marine environment, including characterization of ambient soundscapes, propagation conditions, and relevant oceanographic context
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
Coordinate and conduct field experiments, data analyses, and simulation studies to evaluate acoustic system performance in real-world ocean conditions
Bring deep expertise in marine acoustics to complement Sofar’s ocean science, sensing, and forecasting teams
Contribute to product requirements, technical roadmaps, and research 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
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
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 contributing to research programs, technical partnerships, or externally funded work
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:
$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.
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.
Sofar's Commitment to Climate Justice
We at Sofar Ocean acknowledge that careers in the marine sciences “... have traditionally been, and remain, non-diverse work environments”, thereby limiting the entry and prosperity of underrepresented groups in the space. (Johri et al., 2021) Many of these same groups are disproportionately affected by climate change, and are often excluded from decision making that directly address their interests and needs.
We are committed to addressing these climate injustices and highly encourage people who identify as women, LGBTQ+, Black, Indigenous, and people of color (BIPOC) to apply.