Apply📍 United States
🧭 Full-Time
🔍 Cybersecurity
- 5+ years of data science experience and/or an advanced degree in a relevant discipline (Data Science, Machine Learning, Operations Research, etc.).
- Experience implementing machine learning techniques with real-world data, preferably in computer networking or cybersecurity; specifically clustering and anomaly detection.
- Proficiency with machine learning frameworks and libraries such as PyTorch, scikit-learn, and numpy.
- Experience with natural language processing (NLP) techniques and working with LLMs.
- Strong programming skills in Python and familiarity with statistical analysis.
- Experience in data visualization with a variety of tools and working with front-end developers to bring visualizations to production.
- Familiarity with database and big data technologies (Elasticsearch, SQL, Snowflake, etc.).
- Knowledge of cloud-based hosting and ML services, particularly AWS.
- Understanding of containerization and deployment technologies like Docker and Kubernetes.
- Ability to communicate technical concepts effectively, both to teammates and external audiences.
- Excellent problem-solving skills and adaptability in a dynamic environment.
- Develop and deploy machine learning models for real-time anomaly detection and threat identification.
- Automate the discovery of interesting and anomalous data from our global honeypot network.
- Research and implement new LLM technologies to help read and understand complex internet traffic patterns.
- Integrate new visualizations and statistical models into our product to enhance user experience and data interpretation.
- Ensure data quality by collaborating with infrastructure engineers to develop tests and alerts for detecting defects and determining their origin.
- Optimize data pipelines in collaboration with data engineers for efficient data processing.
- Interface directly with customers to capture analytical requests and translate them into actionable engineering requirements.
- Present findings through social media, blogs, and conferences to engage with the broader community.
- Stay current with the latest AI/ML research and cybersecurity trends to continuously improve our solutions.
- Monitor and tune ML models in production environments to ensure scalability and reliability.
AWSDockerPythonSQLElasticSearchKubernetesMachine LearningNumpyPyTorchSnowflakeProduct DevelopmentData scienceElasticsearchCollaborationDocumentation
Posted 2024-11-21
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