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Artificial Intelligence / Machine Learning Engineer
AmentumAI/ML Engineer supporting AUSLIST program and ASCA Precision Loitering Munitions missions. Engaging in development of AI/ML policy and representation at related Defence activities.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and validating machine learning models using Python and frameworks such as PyTorch and TensorFlow, while effectively engaging stakeholders in multidisciplinary environments. Capable of navigating secure and regulated settings to support AI/ML policy development for UAS projects.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProgrammingAI/ML Frameworks (PyTorch, TensorFlow, Scikit-learn, OpenCV)Complex Dataset AnalysisSoftware Engineering Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Machine LearningPythonPyTorchTensorFlowScikit-learnOpenCVData AnalysisModel ValidationAutomated TestingAgile Delivery
Soft Skills
Analytical SkillsProblem-SolvingCommunicationStakeholder Engagement
Certifications & Qualifications
Bachelor Degree in Computer Science (AI/ML)Eligibility for Security Clearance
Industry Keywords
AI/MLUAS ProjectsDefence ActivitiesRegulated EnvironmentsSafety-Critical Environments
Tech Stack
Tools & technologiesPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Support the development of AI/ML requirements
- Represent the client at AI/ML related Defence activities (conferences and working groups)
- Develop AI/ML policy for the certification to support future UAS projects within the client's program of work including RAS at Scale Delivery Model
Requirements
What you’ll need- Bachelor Degree in Computer Science (AI/ML) or similar
- Demonstrated experience developing machine learning models using Python and common AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, OpenCV, or similar.
- Experience working with complex datasets, including imagery, video, sensor data, telemetry, time-series data, simulation data, or engineering data.
- Strong understanding of machine learning model development, validation, testing, deployment, and performance monitoring.
- Experience with software engineering practices, including version control, code review, automated testing, documentation, and agile delivery.
- Ability to work in multidisciplinary engineering environments involving systems, software, data, hardware, operations, and test teams.
- Strong analytical, problem-solving, communication, and stakeholder engagement skills.
- Ability to work within secure, regulated, or safety-critical environments.
- Eligibility to obtain and maintain an appropriate security clearance.
Benefits
Comp & perks- Healthy work-life balance
- Friendly company culture
- Engagement with a supportive community
- Competitive package to retain and attract talent