Machine Learning Engineer III
General Atomics - Location not specified
Posted Jun 10, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified checked Jun 7, 2026
- Salary
- Not verified
- 401(k) match
- Reported from DOL Form 5500 industry filing (not employer-specific)
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Market context
- U.S. role benchmark (BLS OEWS)
- $116,543 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +9.8% - Much faster than average
Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Machine Learning Engineer III 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. DUTIES AND RESPONSIBILITIES: - Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope. - In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. - In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code. - Completes programming and implements efficiencies, performs testing and debugging. - Completes documentation and procedures for installation and maintenance. - Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope. - Lead technical teams and scope challenging projects into executable sprints. - Drive code reviews to help team adhere to general DevSecOps and MLOps best practices. - Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution. - Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience. - Interface with external vendors and partners to integrate their technology into the team's autonomy stack. - Maintains
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