Machine Learning Summer 2025 Internship at Jericho Security

The Company
Jericho Security is the ultimate battleground where cyberdefense clashes with the constantly evolving menace of generative artificial intelligence. The threat of malicious AI attacks is greater than ever with its evolving efficiency placing all industries in peril. Jericho is taking on the challenge to protect all from the unrelenting assault of next-gen cyber attacks.

The Role:
We are seeking a candidate for a Machine Learning 2025 Summer Internship with optional extension to 1 year that is currently pursuing a Master’s degree in Computer Science, Data Science, or related field. As a machine learning intern, you will be exposed to all parts of the ML development process including data analysis, model development, and deployment. You will work on applying research to the Jericho product suite. This role is ideal for someone who is eager to apply their academic knowledge in a real-world setting, contribute to ongoing projects, and learn from a collaborative team of engineers and researchers.

Responsibilities:

• Assist in the development, testing, and evaluation of machine learning models
• Clean, process, and analyze large datasets
• Contribute to experimentation and documentation of model performance
• Collaborate with cross-functional teams to deploy ML solutions
• Research and prototype new algorithms under guidance from senior team members
• Present findings and updates in weekly team meetings
  
  

Qualifications:

• Currently enrolled in a Master’s program in Computer Science, Machine Learning, Data Science, Statistics or a related technical field
• Strong understanding of machine learning concepts and techniques (e.g., supervised/unsupervised learning, deep learning)
• Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience working with data (data cleaning, feature engineering, etc.)
• Familiarity with Jupyter Notebooks, version control (Git), and cloud platforms is a plus
• Strong communication skills and ability to work independently in a remote setting
• Ability to find solutions to open-ended, potentially complex problems
  
  

Nice-to-have’s:

• Experience with NLP, computer vision, or reinforcement learning
• Familiarity with in-context learning, prompt engineering, and LLM post-training methods
• Familiarity with online experiments via A/B testing
• Prior internship or research experience in ML
• Contributions to open-source ML projects
  

What You’ll Gain:

• Hands-on experience applying ML in a professional environment
• Mentorship from experienced engineers and researchers
• Opportunity to contribute to meaningful projects and publish findings
• A collaborative and innovative work culture