About Us

Moonware is building the future of airside operations. We’re creating an integrated ecosystem of AI software and smart vehicles that connect ground crew, vehicles and aircraft to efficiently service flights. With our advanced technologies, we are transforming aviation ground operations across the passenger, cargo, defense, and advanced air mobility sectors.

Moonware was founded on the belief that multimodal air transportation will become the prime mover of people and goods in the 21st century. To support this shift, airports and the hubs connecting these transport modes must transform to meet the demands of modern air travel. While aircraft technology continues to advance rapidly, the infrastructure and ground operations needed to enable these next-generation aerial ecosystems remain largely outdated. Moonware is closing this gap by creating the ecosystem for automated airfields to support the next era of travel.

Our flagship product, HALO, is the world’s first Ground Traffic Control platform powered by AI. The platform is designed to streamline aircraft turnaround management, seamlessly coordinating ramp crew and ground support equipment to service flights on time. It drives significant operational improvements for teams, resulting in faster turnarounds, reduced block times, fewer delays, increased flight throughput, and maximized asset utilization. The modernization HALO brings to ground operations is what we see as building the bridge to airfield autonomy.

We are a team of builders from top Silicon Valley tech companies, combining our expertise in aerospace and software to drive innovation in an industry often slow to evolve. As we push forward, the Moonware ecosystem will continue to expand, unlocking new possibilities and shaping the future of travel.

About the Role

We’re seeking an accomplished Senior Machine Learning Engineer to be a crucial player in our technology-driven journey. As a Senior Machine Learning Engineer, you’ll lead the development of machine learning models that drive intelligent decision-making in our ecosystem. Collaborating closely with cross-functional teams, you’ll contribute to reshaping the aviation industry through data-driven solutions.

Responsibilities:

  • Design, develop, and deploy machine learning models to enhance the capabilities of our HALO and ATLAS platform.
  • Collaborate with software engineers, data scientists, and domain experts to identify opportunities for applying machine learning techniques.
  • Lead the end-to-end machine learning pipeline, from data collection and preprocessing to model training and deployment.
  • Optimize models for performance, scalability, and real-time operation.
  • Apply software methodology to take an ML algorithm from a prototype to a final production quality deployment.
  • Participate in code reviews, provide technical insights, and contribute to continuous improvement of development processes.
  • Stay updated with emerging technologies and best practices in machine learning.

Requirements:

  • 3+ years of experience in machine learning or related roles.
  • Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Extensive experience with designing, training, and deploying machine learning models.
  • Experience building models for speech recognition and/or natural language processing.
  • Familiarity with data preprocessing, feature engineering, and model evaluation.
  • 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 machine learning 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 data-driven solutions.
  • You enjoy staying updated on the latest trends and best practices in machine learning.
  • You are willing to relocate to Los Angeles

Nice to Haves:

  • Experience in the aerospace, aviation, or transportation industry.
  • Knowledge of IoT and data integration in machine learning models.
  • Familiarity with cloud services (e.g., AWS, Azure, GCP).
  • Previous startup experience.