Looking for a chance to create a positive impact on our society?
The Cyber Defense Machine Learning (ML) Engineer is a member of the Cyber Security Operation Center Organization of SIEMENS. The Primary mission is to detect, analyze, investigate, and defend against sophisticated digital attacks. The ML Engineer designs, implements and operates AI use cases on top of an analytics platform leveraging cloud and on-premises technologies. She/He translates functional requirements from Cyber Analysts into a high performing Cyber Defense platform
As AI/Machine Learning Engineer you will:
- Assess and translate Cyber Defense requirements into AI/ML use cases.
- Develop and deploy Cyber Defense use cases on top of a Big Data Analytics platform.
- Extend the AI cloud platform to meet the ML use case requirements.
- Build and architect AI/ML platform on top of Amazon Web Services (AWS).
- Working around production ML applications.
- Build CI/CD tools for Cyber Defense ML Use Cases.
- Integrate Cyber Defense forensic tools as well as AI/ML tools into the platform.
- Design, prototype, retrain and evaluate existing or new ML models.
- Maintain and design data-driven architectures and code repositories for large projects.
- Collaborate with other SIEMENS departments and customers in order to accomplish your tasks.
- Perform advanced areas of work for the professional field. Applies advanced skills to resolve very complex problems not covered by existing procedures or practices independently. Displays a high level of critical thinking in bringing successful resolution to high-impact, complex, and/or cross-functional problems.
- Demonstrates and applies comprehensive knowledge of field of specialization to the successful completion of complex assignments.
To make a difference, you must have:
- BS/BA in a related field, or advanced degree, or equivalent combination of education and experience. Certification may be required in some areas.
- Typically, 2-5 years of successful work experience with multiple years in a related field or solid theoretical understanding of AI/ML and cloud-based systems, or a related field. Successful demonstration of Key Responsibilities and Knowledge as presented above.
- Experience with modern Data Science/ML frameworks, e.g., Amazon SageMaker services, Tensorflow, PyTorch, Scikit-Learn, Pandas, etc.
- Experience in solving problems with Deep Learning.
- Experience in supervised and unsupervised traditional ML algorithms, e.g., SVM, DBSCAN, XGBoost, Random Forest, Isolation Forest, K-means etc.
- Experience in deploying ML models using different protocols (HTTPS, MQTT, etc.) and tools (Flask, FastAPI, SageMaker Endpoints, etc.).
- Experience with some of the following AWS services: SageMaker, S3, Athena, IAM, EMR, CodeCommit, IoT Core, etc.
- Proven skills in Python programming language and Jupyter Notebook environments.
- Experience with version control tools, e.g., Git.
- Written and verbal communication skills in English.
- Demonstrated ability to learn quickly and adapt to a fast-paced environment.
- Demonstrated ability to train and guide colleagues.
- Demonstrates professional maturity and presentation skills.
Preferred Knowledge/Skills, Education, and Experience
Should have knowledge or experience in several of the following areas:
- Understanding of Networks, Firewalls, Proxies, VPN, intrusion detection systems, endpoint detection and response
- Understanding of plant automation environments and programming logic controller
- Experience with anomaly detection, preferably in a cybersecurity environment
- Experience with data engineering, batch and stream processing tools
- AWS Certification degree is of advantage, e.g., AWS Solution Architect, AWS Developer
We’ve got quite a lot to offer. How about you?
Please, submit your CV in English. Apply here
Curious about our Cybersecurity hub?
- The Siemens Lisbon Tech Hub has more than 1000 digital minds including the Cybersecurity team, making it one of the largest in Europe - check it out
Diversity at Siemens is our source of creativity and innovation. Having different types of talent and experience makes us more competitive and better able to respond successfully to society's demands. That's why we value candidates who reflect the diversity we enjoy in our company.
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