About the Role
The SandboxAQ team is looking for a talented Machine Learning Engineer to join our dynamic team. The ideal candidate will be responsible for developing and training cutting-edge machine learning models to help shape the next generation of cybersecurity systems and enhance our security suite’s capabilities. You will be part of a diverse team consisting of cryptographers and ML experts, playing a key role in efficient and effective enablement of the technologies being developed.
Core Responsibilities
- Design, develop, and implement end-to-end machine learning solutions in the cybersecurity field as an individual contributor
- Work closely with other ML team members and the engineering team to integrate ML solutions into existing solutions
- Analyze large-scale security data incl. network traces, filesystems, and logs / event data
- Optimize and fine-tune machine learning models to improve performance and scalability
- Conduct research to stay updated on the advancements in ML applied to cybersecurity
- Perform thorough testing and validation of ML models to ensure reliability / effectiveness
Qualifications and Skills
- Proven experience working as a ML Engineer, preferably in the cybersecurity domain
- Experience with rapid prototyping to deploy machine learning algorithms
- Familiarity with common ML tools (TensorFlow, Keras, PyTorch, etc.)
- Proficiency in programming languages such as Python / C++
Preferred Qualifications
- At least 5 years of proven experience working as an ML Engineer
- Experience with unsupervised learning and data visualization for large datasets
- Experience with ranking systems
- Experience with MLOps frameworks for processing and analyzing large datasets
- Solid understanding of network protocols, security, and cybersecurity principles
- Excellent communication skills and ability to work in a startup environment
