Software Engineer Internship

Allus AI (YC F25); Atlanta (GA); On-site; USD 90,000 - 150,000; Full time

Job summary

Allus AI in Atlanta is building next-generation vision intelligence systems and is seeking candidates pursuing a BS/MS/PhD in CS/ML/EE/Robotics. You will contribute to real ML projects with Python and PyTorch, focusing on computer vision development.

Candidates should understand modern CV architectures, training workflows, and enjoy startup ownership and building production-ready systems. This role offers the chance to work on cutting-edge research and ship impactful software.

Qualifications

• Pursuing a BS, MS, or PhD in Computer Science, ML, EE, robotics, or a related field.
• Strong programming skills in Python.
• Experience building ML projects or CV research projects.
• Familiarity with PyTorch or similar DL frameworks.
• Understanding of modern computer vision architectures and training workflows.
• Strong problem-solving ability and quick learning.
• Excited about startups, ownership, and building production systems.

Skills

Python

ML projects

Computer vision

PyTorch

Deep learning

Problem solving

Startup mindset

Education

BS/MS/PhD in Computer Science, Machine Learning, Electrical Engineering, Robotics, or related field

Tools

PyTorch

Job description

Overview

Allus AI is building the next generation of vision intelligence systems.

What we\'re looking for

• Pursuing a BS, MS, or PhD in Computer Science, Machine Learning, Electrical Engineering, Robotics, or a related field
• Strong programming skills in Python
• Experience building ML projects, research projects, or open-source contributions involving computer vision
• Familiarity with PyTorch or similar deep learning frameworks
• Understanding of modern computer vision architectures and training workflows
• Strong problem-solving ability and willingness to learn quickly
• Excited about startups, ownership, and building production systems

Nice to have

• Experience training or fine-tuning vision models
• Experience with object detection, segmentation, OCR, or multimodal systems
• Experience with distributed training or GPU optimization
• Publications, research experience, Kaggle competitions, or open-source contributions
• Familiarity with foundation models such as CLIP, DINOv2, SAM, Florence, Qwen-VL, or similar systems

Relevant experience

• Computer vision projects
• Machine learning research
• Foundation model fine-tuning
• Dataset generation and curation
• Model evaluation and benchmarking
• MLOps and training infrastructure
• Open-source ML contributions