Description
Founded in 2015, Shield AI is a venture-backed defense technology company with the mission of protecting service members and civilians with intelligent, autonomous systems. Its products include Hivemind Enterprise—EdgeOS, Pilot, Commander, and Forge—as well as V-BAT and Sentient Vision Systems (wide-area motion imaging software). With offices in San Diego, Dallas, Washington, D.C., Abu Dhabi (UAE), Kyiv (Ukraine), and Melbourne (Australia), Shield AI’s technology actively supports U.S. and allied operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X and Instagram.
Job Description:
As the Lead Hardware Reliability Engineer for the Aircraft Engineering team, you will manage a team of engineers, data scientists and technicians responsible for hardware failures in the field and new design engineering. You will be responsible for developing the strategy and vision for ensuring Shield AI products are highly reliable when they arrive in customer hands. This team will extract valuable insights from the aircraft fleet and work closely with technical and business teams to optimize hardware reliability. This team will utilize the latest technology and automation available to turn insights from hardware telemetry into action.
What you'll do:
- Manage and mentor a talented team of up to 5 engineers with different backgrounds such as Electrical Engineers and Data Scientists
- Define and execute test campaigns to reproduce failures and determine root cause
- Hands on debugging of failures with test equipment as necessary
- Develop individual team members by enabling opportunities suited to everyone. Provide guidance and technical coaching to develop the team’s expertise and ownership of field reliability
- Define the long-term vision for scaling up field monitoring processes as the fleet grows
- Develop and implement field monitoring systems and strategies to quickly detect fleet trends and failures as they arise
- Combine statistical analysis, software, and field telemetry to draw correlations between production data, environmental factors, and field performance
- Drive hardware, software and operational changes through root cause and analysis findings
- Work closely with hardware, software and production leaders to influence reliability improvements across all disciplines
- Perform technical and business analysis trades to steer the organization
Required qualifications:
- Bachelor’s degree in electrical engineering, computer science, physics, mathematics, or a STEM discipline
- 2+ years of experience in a technical leadership role
- 2+ years in a hardware design, reliability, or root-cause analysis role
- Excellent verbal and written communication skills
- Demonstrated capability to parse technical subjects on a deep level
- Demonstrated ability to jump into ill-defined problem spaces and drive positive outcomes
- Self-starter attitude, energy, and the ability to communicate effectively across business and technical disciplines
#LI-JM2
#LD
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
Shield AI
Artificial Intelligence
Machine Learning
Mechanical Engineering
National Security
Robotics
Security
Software
0 applies
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