תיאור המשרה
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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