Software Engineer Internship

Allus AI (YC F25); United States; On-site; USD 60,000 - 90,000; Full time

Job summary

Allus AI is seeking a student in Computer Science, ML, or related fields to join our vision intelligence team and contribute to research-driven projects with production potential. You should be pursuing a BS, MS, or PhD and have strong Python skills, plus experience building ML or CV projects, research, or open-source contributions.

Familiarity with PyTorch or similar frameworks and understanding of modern vision architectures are a plus.

Qualifications

• Pursuing a BS, MS, or PhD in CS/ML/EE/Robotics or related field.
• Strong Python programming skills.
• 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.
• Willingness to learn quickly and take ownership.
• Excited about startups, ownership, and building production systems.

Skills

Python

Computer Vision

ML Research

Open Source Contributions

Education

BS/MS/PhD in CS/ML/EE/Robotics or related field

Tools

PyTorch

Job description

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