Autonomy Engineer, Senior

As a Senior Autonomy Engineer at our venture-backed startup, you will be responsible for the design and implementation of core autonomy capabilities such as path planning, perception, and multi-agent coordination. You'll develop and maintain our autonomy framework, create effective behavioral models, and optimize machine learning for real-time applications. Your collaboration with the platform team and mentorship of team members will also play a crucial role in driving the project forward.

To be considered for the Senior Autonomy Engineer position, you must have a relevant master's or PhD in fields such as Computer Science, Robotics, or Aerospace Engineering. Additionally, a minimum of 5 years of experience in developing autonomous systems along with expert-level skills in C++ and Python programming are crucial. A solid background in control systems, path planning, and machine learning frameworks is also necessary.

As a Senior Autonomy Engineer, you should be proficient in modern programming languages like C++ and Python, with hands-on experience in robotics middleware such as ROS/ROS2. Familiarity with control systems, real-time embedded systems, machine learning frameworks, and computer vision is highly beneficial. Understanding state estimation, sensor fusion, and CI/CD practices will also be important for successful system integration and testing.

You'll enjoy a fantastic work environment that supports innovation, flexible hours, and the ability to work remotely. We offer competitive salaries ranging from $120,000 to $250,000 USD based on your experience, along with a robust equity package. Health benefits include a free OneMedical membership, flexible PTO, and a culture focused on collaboration and inclusivity. Additionally, there are opportunities for professional growth and involvement in cutting-edge projects.

While experience in aerospace or defense applications is preferred for the Senior Autonomy Engineer position, it is not mandatory. Instead, we highly value candidates with a strong technical foundation in autonomous systems, multi-agent coordination, and motion planning. The willingness to learn and adapt is equally important in our fast-paced environment.

Discuss your hands-on experience with algorithms you've implemented for path planning. Provide specific examples of projects where you successfully designed autonomous navigation systems, highlighting any challenges you faced and how you overcame them.

Describe your experience with ROS/ROS2, emphasizing any significant projects where you utilized these frameworks. Be sure to mention the various robotic components you integrated and the overall impact of your contributions on the project.

Provide detailed insights into your process for developing machine learning models, especially in the context of real-time systems. Explain how you ensure models are efficient, responsive, and accurately tuned for the specific needs of autonomous systems.

Outline the strategies you employ for system testing and validation, including simulation environments you utilize, types of tests you run, and how you assess the performance of autonomous systems before deployment.

Share a specific experience where you guided a junior engineer. Discuss your mentoring style, the objectives you set, and how you tracked their progress, highlighting the positive outcomes of your mentorship.

Discuss your insights into the complexities of multi-agent systems, emphasizing key issues like communication, resource allocation, and decision-making processes, and propose potential solutions or methodologies you believe could mitigate these challenges.

Talk about the resources you rely on to keep your knowledge fresh, including publications, conferences, and collaboration with peers. Mention any relevant communities you are engaged in that keep you in the loop about trends and innovations.

Elaborate on the simulation environments you have worked with, such as Gazebo or AirSim. Discuss their specific roles in your projects and how you've leveraged them to test and refine your autonomous systems.

Describe your approach to building scalable architectures for autonomous systems, touching on key design principles, the importance of modularity, and techniques for managing complexity and scalability in code.

Provide a specific strategy you would employ to navigate conflicting demands from stakeholders. Emphasize your communication skills and ability to establish a prioritization framework while satisfying key operational requirements.