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# Senior Software Engineer (Controls)

- **Company:** The Seneca
- **Location:** Sausalito, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Systems Engineering, C++ (Programming Language), Computer Engineering, Hardware-In-The-Loop Simulation, Python (Programming Language), Network Troubleshooting, Machine Learning, Motion Planning, Real-Time Operating Systems, Tensorflow, Software Engineering, System Testing, Pytorch, Deep Learning, Modeling and Simulation
- **Published:** October 22, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-controls-sausalito-ca--7a854215-ede3-4910-93db-0412ba9fb7c5

## About the Role

Software Engineering, Control Engineering, Deep Learning, Machine Learning, Control Systems, Flight Planning, Algorithms, Testing, Simulation, Embedded Systems, * EITHER PhD & 2+ years of work experience: PhD in Mechanical Engineering, Aerospace Engineering, Computer Engineering, Robotics, or a related field AND 2+ years of hands-on experience in control system design, modeling, and simulation.

 * OR Masters & 5-8+ years work experience: Masters in Mechanical Engineering, Aerospace Engineering, Computer Engineering, Robotics, or a related field AND 5-8+ 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.

## Description

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., * 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.