Machine Learning Engineer
صاحب العمل نشط
حالة تأهب وظيفة
سيتم تحديثك بأحدث تنبيهات الوظائف عبر البريد الإلكتروني
شارك هذه الوظيفة
حالة تأهب وظيفة
سيتم تحديثك بأحدث تنبيهات الوظائف عبر البريد الإلكتروني
الوصف الوظيفي
At Thales we know technology has the ability to make our world more secure sustainable and inclusive and that its all driven by human intelligence.
Because it takes human intelligence to build and power the systems and solutions that people depend on every day. So we stay curious and make space for diverse points of view. We share what we know and we challenge whats possible.
Were driving progress in some of the worlds most important industries - from the bottom of the oceans to the depths of space and cyberspace - and from manufacturing to engineering we work together to build a future we can all trust.
Imperva a Thales company is a globally recognized cybersecurity leader dedicated to securing data and applications across diverse environments. Our cutting-edge solutions empower organizations to safeguard their most critical assets ensuring robust protection against emerging threats.
Were proud to be recognized as one ofIsraels Top 50 High-Tech Companies to Work For in 2024(Dun & Bradstreet) and offer a flexiblehybrid work modelfrom ourTel Aviv office.
We are looking for a Machine Learning Engineer as part of our Threat Research group to help us deploy our ML models that protect 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.
Key Responsibilities:
Work together with Data Scientists Data Engineers DevOps and Product teams to deploy ML models in production.
Apply engineering knowledge and expertise to create robust and optimized ML applications that will perform under a set of predefined conditions.
Play a major part in the development of innovative security solutions to be integrated in our best in breed products.
Deploy ML models that will be capable of running offline near real-time and real-time environments.
Be part of building the infrastructure and pipelines 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 features and capabilities into the ML infrastructure.
Influence hundreds of millions of users daily.
Requirements:
. in Computer Science Engineering Math or other quantitative / technical field.
5 years of hands-on experience working with advanced Python including OOP API frameworks async and concurrency & parallelism.
Deep understanding of the ML model lifecycle (training testing deployment etc.) and a basic understanding of model types and architectures.
Practical experience working with and around machine learning models.
Proven track record in building and managing ML pipelines.
Experience working with task orchestration and MLOps tools such as AirFlow Kubeflow MLFlow W&B SageMaker etc.
Familiarity with microservice methodology and container orchestration tools such as Kubernetes.
Experience with cloud-based data platforms such as AWS GCP or AZURE.
Strong problem-solving skills and the ability to work both collaboratively with a team and independently.
Self-learner with a can-do attitude.
Solid experience in querying and manipulating large data sets using SQL and SQL like languages (e.g. Presto) - an advantage.
Solid experience in 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.
Experience deploying LLMs an advantage.
Background in cybersecurity an advantage.
Thales champions inclusion and we believe diversity strengthens the fabric of our culture. We are an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex gender identity sexual orientation race colour religion national origin disability protected Veteran status age or any other characteristic protected by law.
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