As a Machine Learning practitioner, you'll collaborate closely with our data science, research, Innovation, and software development teams to create, train, and deploy machine learning models.
Your work will contribute to the development of AI systems that revolutionize cyber threat detection.
Responsibilities:
Design, train, and deploy machine learning models and pipelines to enhance cyber threat detection capabilities.
Leverage the company's extensive real-world threat data to train and optimize machine learning models.
Work closely with a global team of cybersecurity researchers and data scientists to apply the latest advancements in machine learning and deep learning technologies.
Offer technical expertise and guidance to development teams, ensuring they effectively leverage AI/ML technologies and best practices
Continuously research and implement the newest machine learning techniques to enhance our products and services
Your work will contribute to the development of AI systems that revolutionize cyber threat detection.
Responsibilities:
Design, train, and deploy machine learning models and pipelines to enhance cyber threat detection capabilities.
Leverage the company's extensive real-world threat data to train and optimize machine learning models.
Work closely with a global team of cybersecurity researchers and data scientists to apply the latest advancements in machine learning and deep learning technologies.
Offer technical expertise and guidance to development teams, ensuring they effectively leverage AI/ML technologies and best practices
Continuously research and implement the newest machine learning techniques to enhance our products and services
Requirements:
3+ years of proven experience designing and implementing machine learning models especially in the anomaly detection area.
3+ years of proven experience with Python.
Experience in using ML workflow frameworks such as Kubeflow Vertex pipelines, AirFlow, or Sagemaker pipelines (preferred)
Experience manipulating data sets and building statistical models for large scale datasets
Experience with cloud-based machine learning platforms such as Google cloud, AWS (nice to have)
Knowledge of cybersecurity principles and threat detection techniques (nice to have)
3+ years of proven experience designing and implementing machine learning models especially in the anomaly detection area.
3+ years of proven experience with Python.
Experience in using ML workflow frameworks such as Kubeflow Vertex pipelines, AirFlow, or Sagemaker pipelines (preferred)
Experience manipulating data sets and building statistical models for large scale datasets
Experience with cloud-based machine learning platforms such as Google cloud, AWS (nice to have)
Knowledge of cybersecurity principles and threat detection techniques (nice to have)
This position is open to all candidates.
