AI/ML Intern- GPS Software - Full-time / Part-time
| Verified Pay check_circle | Provided by the employer$21 per hour |
|---|---|
| Hours | Full-time, Part-time |
| Location | Alpharetta, GA Alpharetta, Georgia open_in_new |
About this job
Job Summary:
Expected Start Date: May 18th, 2026
We are seeking a motivated AI/ML Intern to join our GPS Software Engineering team. You will work on real-world projects applying machine learning, predictive analytics, and pattern detection to offender monitoring data collected via GPS tracking devices. This role is perfect for a candidate passionate about using AI/ML to solve impactful public safety challenges.
Intern Logistics:
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Location: Hybrid – Alpharetta, GA
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Hours: Prefer full-time will work with school schedule
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Internship Expected Start Date: ** May/Summer **
Duties/Responsibilities:
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Collaborate with the GPS Engineering teams to design, build, and validate machine learning models.
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Analyze historical GPS tracking data to detect anomalies or improve movement behavior classification.
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Assist in developing intelligent alerting systems based on motion patterns, zones, and device diagnostics. Help users of SCRAM GPS get more details and intelligent information about the alerts and notifications.
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Implement proof-of-concept models and assist in integrating AI components into existing SCRAM Systems software stack.
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Prepare clear documentation of methodologies, datasets, experiments, and results.
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Present project outcomes to engineering leadership at the end of the internship.
Skills/Abilities:
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Solid understanding of machine learning fundamentals, especially in time-series data and anomaly detection.
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Hands-on experience with Python and ML libraries such as TensorFlow, PyTorch, or scikit-learn.
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Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
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Strong problem-solving skills and the ability to work independently and in a collaborative environment.
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Excellent written and verbal communication skills.
Education and Experience:
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Currently pursuing a Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, Data Science, or a related field.
Physical Requirements (With or without reasonable accommodation):
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Sitting: Over 70%
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