This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
As a AI engineer on Security Detections and Operations team you will build and shape the core infrastructure and toolkits to allow detection software engineers, detection and IR data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines. Along with that, you will build systems for these teams to provide access to curated LLMs. You will use your software development expertise to solve difficult problems, tackling complex infrastructure and architecture challenges.
Job Responsibility:
Regularly tackle the largest and most complex problems in the team, from technical design to launch
Deliver solutions that are used by other teams and functional areas
Deliver AI/ML solutions which have a tangible business outcome - i.e. improve detection rate/accuracy, reduce manual toil cost and demonstrate improvement in detection and response metrics
Design and Deploy Tools for Proactive Threat Detection: Leverage AI/ML models to identify anomalous behavior and potential threats in real time, reducing the time to detect breaches
Design Automated Incident Response Workflows: Drive AI/ML-driven automation to enable rapid containment and mitigation of threats, minimizing downtime and impact
Design Threat Intelligence Enrichment: Leverage AI/ML to analyze large volumes of threat intelligence to provide actionable insights to endpoints, email, malware, network and application threats
Requirements:
Fluency in at least one modern object-oriented programming language (preferably Python, Java/Kotlin)
B.S. M.S. in Engineering or STEM discipline with emphasis on Data Science/AI
At least 1-4 years experience in real world AI cybersecurity applications (along with 6+ years of Data Science Experience)
Deep background in statistical modeling and techniques and experience with multimodal data sets
Understanding of Machine Learning project lifecycle and tools
Experience in architecting and implementing high-performance RESTful microservices
Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)
Experience with Continuous Delivery and Continuous Integration
Nice to have:
Experience with Databricks or Apache Spark
Experience with Amazon Sagemaker
Experience with scaling and deploying Machine Learning models
Experience with using LLMs
Experience with frameworks and libraries i.e. TensorFlow, PyTorch, Keras, SciKit Learn, NLTK. Tools Shodan, Metasploit, AWS Bedrock, Amazon Lex
Welcome to CrawlJobs.com – Your Global Job Discovery Platform
At CrawlJobs.com, we simplify finding your next career opportunity by bringing job listings directly to you from all corners of the web. Using cutting-edge AI and web-crawling technologies, we gather and curate job offers from various sources across the globe, ensuring you have access to the most up-to-date job listings in one place.
We use cookies to enhance your experience, analyze traffic, and serve personalized content. By clicking “Accept”, you agree to the use of cookies.