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Software & ML Engineer

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Onsite

Software & ML Engineer

Experis ITR

Software & ML Engineer

Skills

Deep LearningDockerPythonData ScienceJavaC#Machine LearningElasticsearchELK StackFullstack Development

12 days ago

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Important information


Contract type:

Permanent

Location:

Be'er Sheva, Israel

Work mode:

Onsite

Published on:

11 October 2026

What they need


Software & Machine Learning Engineer Full-Time Location: Shoham | Airport City We’re looking for an experienced Software & Machine Learning Engineer to join our team and develop AI-driven solutions in a banking environment. The role combines software engineering, machine learning, and MLOps, with hands-on involvement in developing, deploying, and maintaining intelligent systems. Key Responsibilities Develop and maintain software solutions that integrate AI and machine learning capabilities. Build and implement machine learning models for prediction, clustering, and decision support.

Support the deployment, monitoring, and ongoing improvement of models in production. Develop automation tools to improve system reliability and operational efficiency. Collaborate with team members and business stakeholders to translate business needs into technical solutions. Requirements Bachelor’s degree in Computer Science, Statistics, Data Science, or Machine Learning.

At least 1 year of experience in software engineering or a strong development background gained through a degree in Computer Science or independent projects such as website development. At least 2 years of experience in data science or machine learning development. Strong programming skills in Python and experience with object-oriented programming. Hands-on experience with machine learning algorithms and frameworks.

Knowledge of full-stack web development, including front-end and back-end technologies. Strong analytical thinking and problem-solving skills. Ability to work independently and collaboratively within a team. Excellent written and verbal communication skills.

Advantages Experience with the ELK Stack: Elasticsearch, Logstash, and Kibana. Experience with Docker and automation tools. Experience with MLOps practices and deploying machine learning models in production. Knowledge of additional programming languages, such as Java, C++, or C#.

Experience with deep learning. Familiarity with banking systems and business processes.

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