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מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.

חברה בתחום הייטק / חומרה / תוכנה / סייבר

רמת גן

חברה בתחום הייטק / חומרה / תוכנה / סייבר

רמת גן
מלאה
35,000-50,000 ₪ הערכה מבוססת AI ולא שכר שהתקבל מהמעסיק
הערכה מבוססת AI ולא שכר של המעסיק

Join a team of deep learning specialists developing real-time solutions for cutting-edge automotive applications. We're looking for a hands-on software expert to lead all software-related aspects within the team from infrastructure and tooling to deployment and monitoring. Youll be embedded in a group of data scientists and work closely with DevOps and platform teams to bring deep learning models from concept to customer-ready solutions.
What will your job look like?
Lead the design, development, and maintenance of the teams deep learning software infrastructure.
Build and maintain tools for training, evaluation, deployment, and monitoring of DL models.
Develop and maintain CI/CD pipelines and improve automation across development workflows.
Collaborate with data scientists to streamline model experimentation and product ionization.
Coordinate with DevOps and platform teams to ensure scalability and integration into larger systems.
Develop internal visualization and monitoring tools to support interpretability and performance tracking.
Champion best practices in software development, including testing, code reviews, and maintainability.

Requirements:
BSc in Computer Science, Software Engineering, or a related field.
3+ years of experience in Python development with a focus on MLOps DL or infrastructure.
Experience with at least one major DL framework: PyTorch or TensorFlow.
Solid understanding of deep learning workflows and lifecycle from development to deployment.
Experience with CI/CD, containerized environments (Docker), and version control (Git).
Strong communication and collaboration skills able to work independently and drive projects forward.
Nice to have:
Familiarity with monitoring and visualization tools for DL workflows.
Experience working in or integrating with cloud environments (e.g., AWS, GCP).
Understanding of software architecture for scalable ML systems.
Experience with model deployment and optimization (e.g., quantization, conversion).

This position is open to all candidates.