Staff Software Engineer, Testing

To be considered for the Staff Software Engineer, Testing role at Acubed, candidates must hold a Bachelor's or Master's degree in Computer Science, Software Engineering, or related fields. Additionally, having over 11 years of experience in software development and testing focusing on safety-critical systems is crucial. Expertise in machine learning, programming languages such as Python and C/C++, and familiarity with testing methodologies for neural networks also stand out.

The Staff Software Engineer, Testing at Acubed is responsible for leading the development of scalable testing frameworks for machine learning algorithms used in the aviation industry. This includes designing rigorous validation strategies, collaborating with cross-functional teams to improve AI performance, and ensuring that all AI systems meet aviation certification standards.

At Acubed, safety is paramount. The Staff Software Engineer, Testing will develop and implement comprehensive testing strategies ensuring AI models are validated against strict aviation standards. Close collaboration with systems engineers and safety certification teams ensures that all AI systems are thoroughly vetted to perform safely in real-world scenarios.

As a Staff Software Engineer, Testing at Acubed, you will engage with various technologies including machine learning frameworks such as TensorFlow and PyTorch. Additionally, familiarity with programming in Python and C/C++, along with CI/CD automation tools, plays an essential role in developing robust testing frameworks.

The estimated salary range for the Staff Software Engineer, Testing position at Acubed is competitive, ranging from $164,000 to $203,000 annually. This includes access to a comprehensive benefits package featuring health insurance, a 401(k), flight training, and a yearly target bonus that acknowledges your contributions.

Acubed stands out for its commitment to innovation, collaboration, and diversity. Our team genuinely values the contributions of each member and encourages creativity in shaping the future of digital aviation. By joining us, you'll be part of a team that's making an impactful difference in the aviation industry.

While the specifics can depend on team needs, Acubed traditionally encourages in-person collaboration, especially for critical roles like the Staff Software Engineer, Testing. However, flexibility may be available, and interested candidates should discuss their preferences during the interview process.

In your response, emphasize specific projects where you developed testing frameworks for AI systems. Highlight the tools and technologies you used and any substantial outcomes from the tests you've conducted, ensuring to connect your experience back to safety and reliability standards.

Explain your validation approach, detailing the steps you would follow to deploy rigorous testing methodologies. Mention key factors such as assessing accuracy, checking for edge cases, and ensuring compliance with aviation standards such as DO-178C as part of your strategy.

Choose a project that was technically challenging and discuss the specific obstacles you faced. Highlight your problem-solving strategies and how you collaborated with cross-functional teams to arrive at effective solutions, linking your narrative to the skills Acubed values.

Discuss your approach to effective communication, including methods you use to foster collaboration among team members with diverse expertise. Mention tools such as Agile methodologies, regular meetings, and collaborative platforms to create a seamless working environment.

Explain how automation enhances efficiency and accuracy in testing. Discuss examples of automated testing pipelines you've set up or managed and how they contributed to performing thorough evaluations of AI system behavior under various conditions.

Be specific about your experience with languages such as Python and C/C++. Highlight relevant automation and CI/CD tools you've used in previous roles, particularly in the context of safety-critical systems to show your technical readiness for the role at Acubed.

Talk about the resources you utilize to keep your knowledge up to date, such as industry conferences, publications, online courses, or professional groups. Emphasize your proactive approach to learning and adapting as technology evolves.

Demonstrate your problem-solving skills by outlining a systematic approach to diagnosing the issues that led to the failure. Discuss steps you would take to adjust the testing methods or improve the AI models while ensuring compliance with safety standards.

Discuss any specific challenges you've faced regarding AI safety, such as adversarial attacks or model robustness. Emphasize how you've addressed these concerns in your work and any measures you implemented to enhance the stability of AI systems.

Outline the critical metrics you would use to evaluate AI model performance, such as accuracy, generalization, and robustness under different scenarios. Discuss how these metrics are pertinent to aviation safety and the importance of using data to inform improvements.