TL;DR
Machine Learning Intern (Cybersecurity): Contributing to research and development of ML models for threat detection and data protection with an accent on malware analysis and anomaly detection. Focus on applying agentic approaches to model analysis and building robust ML pipelines within a global R&D team.
Location: Singapore
Company
A global leader in cyber protection, providing integrated solutions for data security and backup with over twenty years of innovation.
What you will do
- Evaluate machine learning models for malware detection, anomaly detection, and threat intelligence.
- Collect, clean, and preprocess large datasets for model training.
- Conduct experiments, analyze performance, and iterate on model improvements.
- Research new machine learning algorithms, focusing on agentic approaches to model analysis.
- Contribute to the development of robust and scalable ML pipelines.
- Document research findings, code, and model architectures.
Requirements
- Currently pursuing a Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, AI, or related field.
- Solid understanding of machine learning concepts, algorithms, and statistical methods.
- Proficiency in Python and familiarity with libraries like TensorFlow, PyTorch, or scikit-learn.
- Experience with data manipulation using Pandas and NumPy.
- Strong problem-solving and analytical skills.
- Excellent communication and team collaboration abilities.
Culture & Benefits
- Global team environment with exposure to industry-leading cybersecurity research.
- Emphasis on innovation, accountability, and continuous improvement.
- Opportunities to solve real-world data protection challenges.
- Collaborative environment involving code reviews and knowledge sharing.
Hiring process
- Interviews are conducted without the use of AI tools or third-party assistance to assess individual skills and communication.
- Employment offers are contingent upon successful completion of criminal, education, and identity background checks.