Software Engineer, Beacon AI

• 3+ years of experience in software engineering, with a focus on AI, machine learning, or predictive modeling
• Bachelor’s degree in Computer Science, Software Engineering, or a related field. Master’s degree is a plus
• Large-scale ML models and deploying them in production environments
• Strong programming skills in languages such as Python, C++, or similar
• Deep learning frameworks (e.g., TensorFlow, PyTorch) and ML pipelines
• Excellent problem-solving skills and ability to translate complex business requirements into scalable technical solutions
• Strong communication skills with the ability to work effectively in cross-functional teams

Desirable

• As a Software Engineer, Prediction & Behavior at Beacon AI, you will play a critical role in developing predictive models and behavior-driven systems that inform our AI-powered flight solutions.
• You will work closely with cross-functional teams to design, build, and deploy scalable machine learning (ML) and artificial intelligence (AI) models that will directly influence aviation safety and operational decisions. This is a great opportunity to grow your experience working on real-time, mission-critical systems in a fast-moving environment
• Behavior and Prediction Models: Develop and optimize algorithms to predict aircraft behavior, trajectory, and operational decisions, ensuring that the models are robust, reliable, and scalable
• R&D Velocity: Create tools, processes, and systems that accelerate R&D efforts and improve productivity across the software engineering and machine learning teams
• High-Quality Code: Write clean, maintainable, and efficient code that runs in production environments, supporting real-time decision-making
• Long-Term Solutions: Invent pragmatic, long-term solutions to complex software and prediction problems, balancing immediate needs with future scalability
• Project Ownership: Take full ownership of technical projects from conception to deployment, making key design decisions and trade-offs to ensure project success
• Cross-Functional Collaboration: Work closely with data scientists, product teams, and fellow engineers to design, develop, and integrate technologies that enable large-scale machine learning and aviation systems