Experienced DevOps Engineer for ML

Experienced DevOps Engineer For ML

Imperva, the leader in Application & Data Security, is looking to hire an experienced DevOps engineer, as part of our Threat Research group to lay the infrastructure for deploying our ML models that protects our customers against cyber attacks.

The threat research group is composed of elite researchers & developers. We research application, DDoS & database attacks, provide algorithms and ML models for new products, and are leading innovation and thought leadership initiatives.

Job Description

• Work together with Data Scientists, Data Engineers, ML engineers, and Product teams to deploy ML models in production
• Be part of building the infrastructure for the ML lifecycle in production, from development to deployment and monitoring
• Manage and monitor the ML infrastructure to maintain production grade performance
• Ensure that our ML models in production remain accurate and reliable by implementing monitoring, testing, and validation tools and techniques.
• Introduce new data sources into the ML infrastructure that ML models can train and or infer upon in a reliable manner
• Introduce new features into the ML infrastructure
• Influence hundreds of millions of users, daily
  
  

• 4+ years of hands-on experience as a DevOps engineer
• Strong Python programming skills
• Solid understanding of Unix/Linux systems and networks
• Experience in writing infrastructure code using tools such as Terraform
• Experience with cloud-based data platforms such as AWS, GCP, or AZURE
• Understanding of Data Orchestration frameworks such as AirFlow
• Familiarity with container orchestration tools, including Kubernetes
• Strong problem-solving skills and the ability to work both collaboratively with a team and independently
• Self-learner with can-do attitude
• Willing to learn about ML and ML tools
• Knowledge of Machine Learning: understanding basic concepts and how models are trained and tested - an advantage
• Background in cybersecurity – an advantage
• Solid experience in querying and manipulating large data sets using SQL and SQL like languages (e.g., Presto) - an advantage
• Familiarity with machine learning and deep-learning libraries, such as Scikit-learn, SciPy, TensorFlow, Pandas, NumPy ,PyTorch, Keras – an advantage.
• Hands on programming skills in Java, C++, and Rust - an advantage