Senior Robotics Software Engineer

Company Description COAST Autonomous designs and develops advanced vehicle automation and monitoring systems that serve as the core intelligence for autonomous vehicles. The company focuses on transforming standard vehicles into driverless ARM (Autonomous Road Machines) that deliver safe, right-speed transportation for people or cargo. COAST Autonomous solutions support point-to-point and on-demand operations, enabling flexible deployment in a variety of environments. The team is dedicated to building reliable, scalable technology that helps customers implement practical autonomous mobility services.

Role Description The Senior Robotics Software Engineer is a full-time, on-site role based in the Tampa area. This role is responsible for designing, implementing, and optimizing software that powers autonomous platforms, including perception, planning, control, and system integration components. Day-to-day tasks include developing and maintaining backend services, writing robust and efficient code, performing code reviews, and collaborating closely with hardware, product, and testing teams to ensure system reliability and safety. The engineer will analyze system performance, debug complex issues in real-world deployments, and contribute to architectural decisions and best practices for the robotics software stack. The role also involves documenting designs, participating in cross-functional technical discussions, and mentoring other engineers.

Qualifications

• Bachelor's, Master's, or Ph.D. in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a related field.
• 3+ years of experience developing robotics or autonomous systems (entry-level candidates with exceptional research or project experience may also be considered).
• Strong programming skills in C++ and Python.
• Solid understanding of robotics algorithms, including:
• Localization and Mapping (SLAM)
• Sensor Fusion
• State Estimation
• Motion Planning
• Trajectory Generation
• Navigation and Obstacle Avoidance
• Experience with AI-based path planning techniques, including graph search, sampling-based planning, optimization-based planning, and reinforcement learning.
• Strong knowledge of control systems, including:
• PID Control
• Model Predictive Control (MPC)
• Optimal Control
• Nonlinear and Adaptive Control
• Familiarity with autonomous vehicle software architecture and real-time robotic systems.
• Experience integrating sensors such as LiDAR, Radar, IMU, GPS, cameras, and ultrasonic sensors.
• Strong understanding of perception pipelines and computer vision fundamentals.
• Knowledge of machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with Linux development environments and Git version control.
• Strong debugging, analytical, and problem-solving skills.