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Oceanus Marine Technologies

engineering opportunity

Computer Vision Software Engineer

Design, train, and optimize computer vision models for real-time maritime applications on edge devices. Collaborate with cross-functional teams to integrate perception systems and validate performance in operational environments.

El Segundo, California, United StatesonsiteFULL_TIME

Posted

About the role

What will you do at Oceanus Marine Technologies?

About Oceanus Oceanus Marine Technologies is building the operating platform for the modern maritime world. Global trade runs on ships, and we’re redefining what’s possible at sea by leveraging modern technology. We’re a small, hands-on team based in El Segundo building full-stack systems that perform in real operating conditions across vessels, ports, and fleets.

We focus on practical, deployable technology that brings safety oversight, automation, and coordination to complex maritime environments. Our founding team previously built and operated SpaceX’s Autonomous Spaceport Droneships, which are among the most advanced autonomous maritime systems ever deployed. Today, we work with leading U.S. operators to bring that same rigor and systems thinking to the next generation of maritime infrastructure.

About the Role

We're looking for a versatile and pragmatic Computer Vision / Perception Engineer to help deliver robust, real-world AI for our edge-intelligent maritime platform. In this role, you’ll have the opportunity to work hands-on across the stack—from designing novel vision algorithms and managing real-world datasets, to optimizing perception systems for edge devices running on challenging commercial vessels.

You’ll thrive if you enjoy a broad set of responsibilities, between several problem domains, and turning ambitious concepts into reliable deployed systems. Our team is rethinking how the maritime world operates — come help us build the backbone for safer, smarter global shipping.

Key Responsibilities

  • Design, train, and evaluate computer vision models for real-time maritime applications: object detection, tracking, event classification, anomaly detection, and more Optimize perception model architectures and inference pipelines for constrained edge devices (onboard compute, limited connectivity, heterogeneous sensors) Develop and curate diverse datasets (standard, field-collected, simulated, and synthetic), including data augmentation and domain adaptation strategies Build, maintain, and experiment with robust, real-time pipelines for sensor fusion (cameras, radar, etc.) and multi-modal perception Collaborate closely with hardware, software, and marine engineering teams on iterative prototyping, system integration, and field validation Implement tools for debugging, benchmarking, visualization, and automated monitoring of model performance and system reliability Stay actively engaged with emerging research, tools, and best practices in computer vision and perception—and apply new ideas to product roadmaps Contribute to code reviews, technical documentation, and team-wide knowledge sharing Support deployments and testing in live operational environments, iteratively refining models based on field results and user/operator feedback Minimum Qualifications Bachelor’s, Master’s, or PhD in Computer Vision, Machine Learning, Robotics, or relevant field (bachelor’s considered with strong relevant experience) 2+ years of experience developing and deploying computer vision and/or perception systems in production or field settings Highly proficient in Python and/or C++; strong command of deep learning frameworks such as PyTorch and/or TensorFlow, and computer vision libraries like OpenCV Demonstrated expertise across the ML lifecycle: dataset management, model development, testing, optimization, deployment, and monitoring Hands-on experience with edge or embedded device ML (model compression, inference optimization, hardware integration) Comfort working with mixed data types (images, video, time-series, sensor data) Strong experimental, debugging, and problem-solving mindset Effective communicator and team collaborator—able to bridge technical and operational conversations Preferred Skills and Experience Experience with sensor fusion (cameras, radar, LIDAR, etc.) and multi-modal perception Experience fielding ML models in maritime, robotics, automotive, aerospace, or other remote/harsh environments Familiarity with networking, real-time systems, and remote ops pipelines Prior work on real-time event detection, anomaly detection, or maritime system integration Work Environment On-site with the team at our office in El Segundo, CA Occasional travel to test sites or operator locations as needed Compensation and Benefits We are open to a wide range of experience levels.
  • The expected salary range for this role is $130,000 - $220,000.
  • Final compensation will be determined based on experience, skills, and scope of the role.
  • We offer a comprehensive benefits package that includes: Comprehensive medical, dental, and vision coverage Generous Equity participation Fully stocked kitchen and catered lunch every day Onsite EV charging Flex Paid time off and company holidays 401(k) traditional and roth options Additional benefits that support your health, growth, and well-being Why Oceanus, Why Now Maritime operations are at the edge of a revolution.
  • New connectivity and compute are finally unlocking remote monitoring, autonomy, and digitization.
  • Regulatory, economic, and geopolitical pressure is accelerating technology adoption, and U.S.-aligned infrastructure is more valuable than ever.
  • Oceanus is building on hard-won operational experience, including work on autonomous maritime systems supporting missions like SpaceX droneships, and have deep operator engagement with strong product-market alignment.
  • You will help form the technical core of a team transforming an industry that quite literally moves the world.

Which skills does this role require?

Computer visionPythonC++PyTorchTensorFlowOpenCVMachine learningEdge computingModel optimizationData augmentationObject detectionEmbedded systemsPerception systemsComputer VisionSoftware EngineerAIEdge ComputingObject DetectionEmbedded SystemsMachine LearningData AugmentationDomain AdaptationModel CompressionInference OptimizationHardware IntegrationField ValidationAutonomous SystemsPrototypingProduct Strategy

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