As an ML Platform Engineer, you will work closely on a cross-functional team with ML engineers and Data engineers to deploy real-time models at scale and build systems/tooling to support advanced use cases and increase development velocity.
You will build the next generation ml platform developing systems for ml development lifecycle, continuous training, real-time feature stores and more.
- Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
- Strong software engineering skills in complex real-time systems
- Fluency in Python
- Experience working with AWS cloud technologies such as Sagemaker or equivalent
- Familiarity with orchestration tools such as airflow and mlflow
- Exposure to machine learning methodology and best practices
- Design the data pipelines and engineering infrastructure to support machine learning systems at scale
- Develop and deploy scalable tools and services to handle machine learning training and inference
- Identify and evaluate new technologies to improve the performance, maintainability, and reliability of machine learning systems
- Support model development, with an emphasis on reproducibility, versioning, and data quality
- Communicate with stakeholders to build requirements and track progress
What we offer
- Competitive salary
- 20 working days paid vacation
- Medical insurance
About the project
Worldwide anti-phishing company introduces a very secure email platform (powered by AI and ML) that provides an innovative solution to prevent fraud and email attacks.
With the help of the Israel Defense Forces and a top incubator program, this award-winning platform helps prevent and block any attacks in the fastest way.
The company provides all types of businesses with a complete solution against any kind of phishing attack in the mailbox.