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    Senior Embedded Hardware Engineer - Los Angeles, United States - Moonware

    Moonware
    Moonware Los Angeles, United States

    1 week ago

    Default job background
    Description

    Employment:
    Full time


    Team:
    Hardware


    Location:
    Los Angeles, CA (in-person)

    About Us
    Moonware is a venture-backed startup enabling next generation air travel with automated and sustainable airfields.

    We're building an integrated ecosystem of AI software and smart vehicles that efficiently connect ground crew, aircraft, and ground support equipment to efficiently service flights.

    Our long-term vision is to handle aircraft autonomously from touchdown to takeoff, providing seamless aircraft turnarounds for a streamlined airport experience.

    Moonware was founded with the belief that multimodal air transportation will become the prime mover of people and goods during the 21st century.

    From eVTOLs that will ferry passengers between cities and suburban areas, to supersonic aircraft shaving travel time between continents, we are ushering in a new air and space age that will further globalize humanity.

    Airports and the hubs uniting these modes of transport will need to evolve to meet this new modern demand for air travel.

    In spite of the current advancements in aircraft technology, the infrastructure and ground processes that will enable these new aerial ecosystems to happen are largely outdated.

    We are builders hailing from Tesla, Waymo, NASA, Google, Uber and Corvette, leveraging years of product development experience in aerospace, automotive, and robotics to revolutionize the airfields of tomorrow.

    Software Team
    Moonware's software team is building HALO, the OS for aviation ground handling operations.

    HALO is an AI-powered Ground Traffic Control platform designed to streamline aircraft turnaround management, seamlessly coordinating ramp crew and ground support equipment (GSE) to service flights on time.

    HALO's core optimizer fuses flight information, GSE locations and crew tasks to create optimal service missions. Position trackers, instrumented on GSE, provide vehicle location information that is used to define app-specific features.

    Crew & GSE are scheduled & dispatched through the mobile app to service aircraft according to real-time flight schedule changes, with a smart routing feature that navigates ground crew drivers to their destination on the airfield, saving time.

    Real-time task allocation and dynamic vehicle routing are examples of features that take place in the cloud, effectively replacing the current use of radio and paper.

    These time-sensitive operations are migrated over to digital infrastructures that can process the large datasets necessary for task & equipment allocation along with their inherent complexities.

    This approach enables us to collect large amounts of data that is virtually absent on ground vehicle whereabouts and movements, interactions between ground handling agents, and service time punctuality.

    Furthermore, by collecting ground data from different airport hubs, we can build robust machine learning models that take into account airfield traffic patterns and airport-specific constraints.

    We can then use this data to inform where the greatest bottlenecks in ground operations are occurring and how these processes can be augmented by 'last-mile' ramp services with autonomous GSE.

    This is what we call laying the bridge to airfield autonomy.
    About the Role
    We're seeking an accomplished Senior Computer Vision Engineer to play a pivotal role in developing our state-of-the-art technology.

    As a Senior Computer Vision Engineer, you'll lead the development of computer vision solutions that drive intelligent decision-making in our ecosystem.

    Collaborating closely with cross-functional teams, you'll contribute to reshaping the aviation industry through cutting-edge visual perception.

    Responsibilities:
    Lead the design and development of computer vision algorithms and solutions for ground support equipment and smart vehicles.
    Collaborate with software engineers, robotics experts, and domain specialists to integrate computer vision technology into our platform.
    Develop and optimize algorithms for object detection, tracking, recognition, and scene understanding.
    Lead the prototyping, testing, and validation of computer vision solutions, iterating designs based on feedback and data analysis.
    Participate in code reviews, provide technical insights, and contribute to the continuous improvement of development processes.
    Work closely with product managers to understand user requirements and translate them into technical specifications.
    Stay updated with emerging technologies and best practices in computer vision.

    Requirements:
    3+ years of experience in computer vision or related roles.
    Proficiency in computer vision libraries and frameworks (e.g., OpenCV, TensorFlow, PyTorch).
    Extensive experience with designing, developing, and integrating computer vision solutions.
    Solid understanding of image processing, feature extraction, and machine learning techniques.
    Familiarity with sensors, cameras, and hardware integration for computer vision systems.
    Knowledge of version control systems (e.g., Git) and agile development methodologies.
    Excellent problem-solving skills and attention to detail.
    Excellent communication and collaboration skills.

    This Role Might Be for You If:
    You are passionate about driving innovation through computer vision in a dynamic environment.
    Problem-solving and collaboration are at the core of your work ethic.
    You thrive in a fast-paced startup environment where your contributions have a tangible impact.
    You're excited about shaping the future of aviation technology through cutting-edge visual perception solutions.
    You enjoy staying updated on the latest trends and best practices in computer vision.
    You are willing to relocate to Los Angeles

    Nice to Haves:
    Experience in the aerospace, aviation, or transportation industry.
    Knowledge of robotics and autonomous systems.
    Familiarity with machine learning techniques for computer vision.

    #J-18808-Ljbffr
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