Generative Computer Vision Engineer

We're looking for a Computer Vision Researcher/Engineer in the field of natural language-based computer vision applications (VLMs, Open Vocabulary, CLIP)

Key aspects sought after:

• Temporal video understanding
• Few-shot learning
• Embedding search
• Work with VLMs/MLLMs/LLMs
• Deep understanding of Nvidia-based hardware real-time video processing optimization

Location: Hybrid (Israel-based preferred)

Job Type: Part-Time / Flexible (with potential for full-time)

Overview

We’re seeking a generative natural-language computer vision researcher/engineer with deep hands-on expertise in VLMs like CLIP, BLIP, LLaVA and Flamingo, a strong foundation in embedding-space design, contrastive learning and transformer-based encoder/decoder architectures, proven experience developing prompt-to-detect pipelines and benchmarking zero-shot, few-shot and open-vocabulary detection on video data, proficiency in Python and PyTorch/TensorFlow alongside LLM API integration for multimodal workflows.

What You’ll Do

· Read, distill, and apply academic and industry research into production-ready code

· Develop object grounding, re-identification, and NLP-related CV technologies

· Contribute to IP, publications, research papers, and internal innovation.

· Collaborate with our founding tech team to take ideas from paper to product.

· Analyze and benchmark zero-shot, few-shot, and open-vocabulary detection methods

· Build tools for semantic video search,vision-language models, and generative CV

· Build, create and design ground-breaking technologies that don't exist yet

Requirements

· 6+ years of background in computer vision, ML, AI, & multimodal learning

· Hands-on experience with generative AI, LLMs, VLMs/MLLMs.

· Experience with high-scale video analysis in large, distributed systems

· Curiosity and passion - you love exploring, building, and learning, even on your free time.

· M.Sc. or Ph.D preferred - academic background in CS/EE/Math/related.

· Experience with NVIDIA Jetson, edge-AI, or real-world CV/CCTV systems, for real-time video optimization

Required Knowledge

· Vision-Language Models (CLIP, BLIP, LLaVA, etc.)

· Embedding models & semantic search in video

· Prompt-to-detect, zero/few-shot detection

· Scene understanding, re-identification, temporal understanding, multi-camera setups

· Experience working with encoders/decoders, transformers, or contrastive learning frameworks

· Detection under challenging conditions (low-light, thermal, etc.)

Beyond the skills, we’re searching for someone who:

· Is genuinely excited about AI, vision, and building something groundbreaking.

· Brings curiosity, initiative, and a collaborative spirit to every challenge.

· Is the kind of person we’d love to grab a beer (or coffee) with - someone fun, thoughtful, and great to have on the team.