AI Algorithm Team Leader
Location: Or-Yehuda (IL)
Description
ISI is a global leader in space based intelligence solutions, serving for over 20 years as a trusted partner to some of the world’s most demanding defense and intelligence organizations. The company delivers high quality, mission critical capabilities tailored to address complex, strategic, and highly sensitive intelligence challenges. As part of its continued growth, ISI is seeking a talented Algorithm Team Leader to join the Algorithm Development Group and lead cutting edge AI and Computer Vision initiatives that transform advanced research into operational impact.
This position combines technological leadership, research direction, and end to end implementation in a production oriented environment.
Requirements
- BSc in Computer Science, Electrical Engineering, or a related field. MSc is an advantage
- Significant experience in developing algorithms in Computer Vision
- Hands on experience with modern Deep Learning models as YOLO
- Experience working with VLM and LLM
- Proven experience leading a team or providing significant technological leadership
- Demonstrated ability to mentor algorithm developers, including junior team members
- Deep understanding of research methodology, experimentation, and performance evaluation
- Strong leadership and mentoring capabilities
- System level thinking and broad technical perspective
Responsibilities
- Professional and managerial leadership of an AI algorithm team
- Development, training, and optimization of Deep Learning models for computer vision tasks
- Hands on work with advanced detection and segmentation architectures, including YOLO
- Research and implementation of VLM and LLM in multimodal contexts
- Designing research workflows, experimentation frameworks, validation processes, and performance improvements
- Mentoring and guiding junior team members and supporting their professional growth
- Close collaboration with software, product, and hardware teams
Advantages
- Experience working with GIS systems and geospatial data
- Experience implementing algorithms on hardware or working closely with hardware teams
- Experience optimizing models for real time systems or resource constrained environments
- Experience transferring models from research environments to production
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