Introduction to Shield AI
Founded in 2015, Shield AI is a venture-backed defense technology company whose mission is to protect service members and civilians with intelligent systems. In pursuit of this mission, Shield AI is building the world’s best AI pilot. Its AI pilot, Hivemind, has flown a fighter jet (F-16), a vertical takeoff and landing drone (V-BAT), and a quadcopter (Nova). The company has offices in San Diego, Dallas, Washington DC and abroad. Shield AI’s products and people are currently in the field actively supporting operations with the U.S. Department of Defense and U.S. allies.
As the lead of the test group, you will be responsible for ensuring the highest level of quality, reliability, and performance of the Hivemind Enterprise product. You will work across our Hivemind Commander (e.g. ground control station), Design (simulation and analysis tools), Edge (AI and autonomy), and Foundation (middleware) teams to develop test strategies and test suites for our state-of-the-art AI features and SDKs.
What You'll Do:
- Develop and implement testing strategies for AI and autonomy systems, encompassing both software-in-the-loop and hardware-in-the-loop tests.
- Lead a team of test engineers in executing test plans, including component tests, integration tests, and end-to-end system tests.
- Collaborate with cross-functional teams, including software developers, autonomy engineers, product managers, to define test requirements and validate system functionality.
- Establish and maintain a suite of simulation environments for testing and validation purposes, ensuring realistic scenarios and edge cases are adequately covered.
- Work closely with the simulation team to integrate test scenarios, validate simulation models, and ensure consistency between simulated and real-world environments.
- Oversee the design and implementation of hardware-in-the-loop (HIL) testing setups to validate system performance in real-world conditions.
- Conduct data review and statistical analysis of test results, identifying trends, anomalies, and areas for improvement.
- Develop reporting dashboards and metrics to track testing progress, system performance, and reliability metrics.
- Drive continuous improvement initiatives in testing processes and methodologies, leveraging best practices such as test-driven development (TDD) and agile methodologies. Educate development teams about designing for testability.
- Conduct risk assessments and develop mitigation strategies to address potential failures or safety hazards in autonomous systems.
- Provide leadership and mentorship to the test team, fostering a culture of innovation, collaboration, and excellence.
Required Qualifications:
- Minimum of 10 years of related experience with a Bachelor’s degree in Computer Science (or related field); or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
- Minimum of 5 years of experience managing and leading teams
- Proven track record of leading successful test programs for complex autonomous systems, from conception to deployment.
- Extensive knowledge of software development practices, including test-driven development (TDD), continuous integration (CI), and version control systems (e.g., Git).
- Experience with hardware-in-the-loop (HIL) testing setups, including integration with physical sensors, actuators, and control systems.
- Strong analytical and problem-solving skills, with the ability to identify and address technical challenges in autonomous systems.
- Proficiency in Python with data analysis tools and techniques for reviewing and interpreting test data
- Experience with Unix-based systems, command line tools, etc.
- Excellent communication skills, with the ability to effectively collaborate with multidisciplinary teams and external stakeholders.
- Leadership experience, including mentoring junior team members and driving organizational change initiatives.
Preferred Qualifications:
- Familiarity with robotics frameworks (e.g. ROS) and simulation tools (e.g. Gazebo, Unity, Unreal).
- Familiarity with command and control software.
- Familiarity with cloud technologies, simulation, and data analysis pipelines.