ML Engineer Intern: Edge AI & Computer Vision

Alta Ares; Paris (TX); On-site; USD 28,000 - 41,000; Full time

Job summary

Alta Ares is seeking a Machine Learning Engineer Intern to join our Data & AI team and contribute to end-to-end ML pipelines for computer vision tasks. You will help train, evaluate and deploy models, focusing on reliability, reproducibility and scalable infrastructure.

The role is ideal for someone passionate about applied ML, CV and MLOps, eager to gain hands-on experience building AI systems for real-world defense applications in a fast-paced environment.

Qualifications

• Strong foundations in Python, data science and machine learning.
• Experience with deep learning frameworks (PyTorch or TensorFlow).
• Ability to analyse and preprocess image/video data at scale.
• Familiarity with experiment tracking tools (MLflow, Weights & Biases) and data versioning (DVC).
• Understanding of Docker, Git and cloud platforms (AWS or GCP).
• Ability to work autonomously in a research/prototyping environment.

Responsibilities

• Model training and optimization for computer vision tasks (detection, segmentation, tracking).
• Develop evaluation frameworks and automate experiment tracking.
• Build reproducible data workflows for large image/video datasets.
• Contribute to deployment workflows for edge devices and embedded systems.
• Monitor model reliability and performance in production-like settings.
• Document best practices and collaborate on scalable ML infrastructure.

Skills

Python

Data science

Machine learning

Computer vision

Deep learning

Autonomy

Collaboration

Problem solving

Tools

PyTorch

TensorFlow

MLflow

Weights & Biases

DVC

Docker

Git

AWS

GCP

Job description

Alta Ares is seeking a Machine Learning Engineer Intern to join our Data & AI team and contribute to end-to-end ML pipelines for computer vision tasks. You will help train, evaluate and deploy models, focusing on reliability, reproducibility and scalable infrastructure.

The role is ideal for someone passionate about applied ML, CV and MLOps, eager to gain hands-on experience building AI systems for real-world defense applications in a fast-paced environment.