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About the Role

Sofar designs, builds, and deploys ocean sensing networks globally. We are expanding into underwater acoustics to detect, classify, and locate underwater objects, and to create acoustic maps. We seek an experienced ocean acoustics scientist to advance our underwater acoustics platform.

Responsibilities

• Shape Sofar’s acoustics research and development strategy, providing scientific and technical direction for an underwater acoustics platform supporting marine applications.
• Develop capabilities for detecting, classifying, and localizing 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 oceanographic context.
• Provide an acoustics-centric perspective on sensing system design, deployment strategy, data quality, and performance validation.
• Collaborate with 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.
• Bring deep expertise in marine acoustics to complement Sofar’s 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 ocean acoustics community.

Requirements

• 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 practical ocean sensing constraints.
• 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 ability to work 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, or 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.
• Familiarity with embedded sensing systems, firmware constraints, or edge processing for acoustic applications (Bonus).
• Familiarity with the constraints of autonomous ocean platforms (Bonus).
• Comfort working in production codebases when necessary (Bonus).

Skills

• Underwater acoustics
• Acoustic sensing systems
• Detection algorithms
• Classification algorithms
• Localization algorithms
• Mapping algorithms
• Environmental characterization
• Marine acoustic propagation
• Ambient noise analysis
• Signal processing
• Statistical signal processing
• Machine learning
• AI methods
• Field experiments
• Data analysis
• Simulation studies
• LLM utilization

Location

• Hybrid

Work Type

• Hybrid
• Full-time

Experience Level

• Experienced scientist

Education Level

• Ph.D. in acoustics, ocean engineering, electrical engineering, applied physics, oceanography, or a related field, or equivalent experience

Salary/Compensations

• $121,000 - $171,000

Benefits

• Visa sponsorship

About the Company

• Sofar designs, builds, and deploys ocean sensing networks at a global scale.
• We are expanding our sensing capabilities into underwater acoustics.
• Sofar operates at the intersection of ocean science, climate, and technology.
• We are committed to addressing climate injustices and building a diverse team.

Equal Opportunity

• Sofar Ocean acknowledges that careers in the marine sciences have traditionally been non-diverse work environments, limiting the entry and prosperity of underrepresented groups.
• 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.
• 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.