General Atomics and Affiliated Companies Machine Learning and Cloud Services Project Engineer in San Diego, California

Job ID#: 19935BR

Company: General Atomics Aeronautical Systems

Title: Machine Learning and Cloud Services Project Engineer

Job Category: Engineering

City: San Diego

State: California

Full-Time/Part-Time: Full-Time Salary

Travel Percentage Required: 0% - 25%

Clearance Required?: No

Job Summary:

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

Looking for a fast-paced, innovative, and hands-on Project Engineer to join the Automation and Autonomy (A&A) engineering team at General Atomics Aeronautical Systems, Inc., (GA-ASI) specially supporting Machine Learning and Cloud Services.

Automation and Autonomy seeks to continuously disrupt and innovate within unmanned aviation. A&A is responsible for leading technical development of a wide range of products designed to improve the ease of use and drive automation within GA-ASI platforms. We focus on increasing efficiencies in day to day operations through innovative approaches that blend commercial technology with defense applications. We drive new and intelligent capability by integrating machine learning with existing and future platforms while expanding the compute capabilities both onboard and off-board the system.

Duties and Responsibilities

  • Under general supervision, this position exercises considerable latitude in determining technical objectives for the review, research, design, development, and support of machine learning applications. Responsible for integration of the engineering solution within the overall engineering environment; and ensures that appropriate documentation, testing, maintenance, and engineering updates completed.

  • Responsible for project engineering and system integration of machine learning applications as well as application deployment within cloud environments.

  • Knowledge of software development, machine learning, and cloud computing.

  • Experience designing, building, and/or deploying a machine learning application.

  • Delivering product under challenging schedules and high rigor is desired.

  • Communicates effectively with engineering professionals, users, and management throughout the product development cycle.

Job Qualifications:

  • Typically requires a Bachelor’s or Master’s degree in engineering or a related technical discipline from an accredited institution and two or more years of engineering experience with a Bachelor’s degree. May substitute equivalent engineering experience in lieu of education.

  • Must have a thorough understanding of engineering concepts, principles, codes, and theory; experience demonstrating a broad application of those concepts; and, expanding knowledge of principles, concepts, theory, and practices in related technical specialties.

  • Understanding of software theory and/or communication systems is desired.

  • Networking and cybersecurity knowledge is desired.

  • Able to work extended hours as required.

  • A Professional Engineering License and original work published in professional engineering journals are desirable.

  • May be required to obtain and maintain a security clearance. US Citizenship required.

  • Willing to travel (including supporting flight tests) up to 25%.

General Atomics and affiliated companies is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity/Affirmative Action Employer and will consider all qualified applicants for employment without regard to race, color, religion, gender, pregnancy, sex, sexual orientation, gender identity, gender expression, national origin, age, genetic information, protected veteran status, disability, or any other basis protected by local, state, or federal law.