The Job:
We are seeking an exceptional and innovative Controls Engineer to design, develop, and implement control systems for our unmanned aerial vehicles (UAVs). The ideal candidate will have a strong background in control theory and hands-on experience with UAV systems. Experience applying machine learning (ML) and deep learning (DL) to enhance autonomous navigation, path planning, and flight performance is a distinct advantage.
What You'll Do:
Flight Control System Design: Design, implement, and test advanced control algorithms for UAVs to ensure stability, maneuverability, and reliable performance.
Modeling and Simulation: Create and maintain dynamic flight models for various UAV platforms to simulate and validate control strategies.
Path Planning and Autonomy: Integrate path planning algorithms for autonomous navigation, obstacle avoidance, and optimal flight route generation.
ML/DL Integration: Apply machine learning and deep learning techniques to enhance flight control and dynamic flight models.
Embedded Systems: Develop and optimize robust, compute-constrained code for embedded systems, ensuring reliability and real-time performance.
Hardware-in-the-Loop (HIL) Testing: Conduct comprehensive system testing, including Hardware-in-the-Loop simulations and flight testing, to validate control system performance.
Troubleshooting and Optimization: Analyze flight data to troubleshoot system issues, optimize control parameters, and continuously improve overall performance.
Collaboration: Work closely with cross-functional teams, including mechanical, software, and systems engineers, to deliver high-quality and reliable drone solutions.
What You Bring:
PhD or Masters in Mechanical Engineering, Aerospace Engineering, Computer Engineering, Robotics, or a related field.
2+ years of hands-on experience in control system design, modeling, and simulation.
Strong proficiency in programming languages like C++ and Python.
Familiarity with embedded systems and real-time operating systems
Bonus Points For:
Hands-on experience with UAVs, autopilots (e.g., PX4, ArduPilot, Betaflight), and sensor integration.
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) for robotics or autonomous systems.
Knowledge of computer vision principles and techniques.
Familiarity with aviation regulations and safety protocols.
What We Offer:
Competitive Salary – Reflective of your skills and experience
Equity Compensation – Be a part-owner in the company's future
Comprehensive Health Coverage – Including medical, dental, and vision plans
Health Savings Account (HSA) – Optional pre-tax savings for medical expenses
Unlimited PTO – Flexible time off to recharge, plus paid company holidays
About Us
Seneca is eliminating the $1 trillion threat of wildfire across 500 million acres with AI-powered autonomous drone systems. Imagine a world where firefighters can respond to a blaze in under 6 minutes using autonomous suppression technology. That's the world Seneca is building. We’re combining the deep expertise of seasoned fire professionals with the innovation of billion-dollar technology builders to create advanced systems that save lives, property, and natural resources.
This is more than a job—it's a mission to transform safety across 500 million acres. Whatever your background, if you’re a builder, an innovator, or a problem-solver, you belong here.
Don’t meet every single requirement? If you're excited about this role but your experience doesn’t align perfectly with every qualification, we encourage you to apply — you may still be the right fit for our team.
Top Skills
What We Do
Seneca is a resilience technology and infrastructure company. We create autonomous drones and AI-driven software to support firefighters and protect the things we love.
Our mission is to eliminate wildfire threat across 500 million acres in the US and allied nations.
We do so by building products that support the firefighter in use cases that were previously unsafe, inefficient, or impossible.
We prioritize innovations that protect lives, property, and ecosystems. Our focus is on both initial attack operations and beneficial fire support to create a balanced wildland fire cycle over next the coming decades.
