Intuition Machines is hiring a
Machine Learning Intern

Summary

Intuition Machines seeks a Machine Learning Intern to work on applied computer vision projects, leveraging the latest methods. The intern will experiment with ML models, write maintainable code, and participate in code reviews. A strong knowledge of computer vision, Python programming, and ML fundamentals is required.

Requirements

• Thoughtful, conscientious, and self-directed individual
• Strong knowledge of computer vision
• Solid Python programming experience
• Experience with at least 2 of: applying ML to computer vision problems, fine-tuning generative vision models, creative coding and developing generative algorithms, prompt engineering (for language and vision models)
• Understanding of ML fundamentals: bias-variance tradeoffs, loss functions, evaluation metrics, etc
• Bachelor's Degree or an equivalent in a STEM field from an accredited college or university, or equivalent job experience
• Excellent communication, listening, and presentation skills to engage with diverse audiences

Responsibilities

• Experiment with, implement, and evaluate ML models in the visual domain, along with other computer vision approaches
• Iterate quickly, focusing on early and frequent deployment
• Write well-structured, maintainable, well-documented, and tested code, including unit, integration, and end-to-end tests
• Participate in code reviews and architecture & design sessions

Preferred Qualifications

• Strong grasp of the math required for ML (linear algebra, probability theory, statistics, matrix calculus)
• Software engineering/development experience with large-scale distributed systems
• Ability to collaborate with ML DevOps engineers to integrate your work into infrastructure, including automating observability, deployment, quality, and security

Benefits

• Fully remote position with flexible working hours
• An inspiring team of colleagues spread all over the world
• Mentoring and support in learning advanced ML, computer vision, and cybersecurity methods
• Pleasant, modern development and deployment workflows: ship early, ship often
• High impact: lots of users, happy customers, high growth, and cutting edge R&D
• Flat organization, direct interaction with customer teams
• We celebrate diversity and are committed to creating an inclusive environment for all members of our team