Staff Algorithm Engineer (Computer Vision)

Location: Tel Aviv, Israel

Company

A growing startup building real-time subsurface infrastructure mapping technology for the construction industry, with offices in Tel Aviv and Austin.

What you will do

• Research and implement computer vision and algorithmic solutions across perception, learning, optimization, and graph-based reasoning.
• Design experiments, evaluate results, and own algorithm quality through production deployment.
• Monitor production model health, identify degradation, and lead remediation efforts.
• Collaborate with algorithm, data engineering, and product teams to share models, methods, and insights.
• Integrate AI tools into engineering workflows and develop as an architect and team lead.
• Raise technical standards through code reviews, knowledge sharing, and mentoring.

Requirements

• Relevant B.Sc. or M.Sc. with 10+ years of experience as a Computer Vision or Algorithm Engineer, or a relevant Ph.D. with 7+ years of industry experience.
• Broad and deep computer vision expertise with strong algorithmic foundations.
• Deep proficiency in deep learning frameworks, preferably PyTorch.
• Production-grade Python development skills and proven end-to-end ownership of computer vision problems.
• Strong problem-solving, communication, self-direction, and entrepreneurial skills.
• Experience mentoring and developing team members.

Nice to have

• Experience with GIS datasets or geospatial computer vision.
• Familiarity with GNN or graph-based algorithms.
• Experience with AWS services such as SageMaker, S3, or EC2.
• Background in active learning or AI-assisted annotation pipelines.

Culture & Benefits

• Work on original computer vision and algorithmic problems with direct product impact.
• Own the full path from research spikes to production systems.
• High-autonomy environment with responsibility from the start.
• Opportunity to grow into an architect and team lead role.
• Participate in building an AI-first engineering culture using code assistants, LLMs, and AI-augmented workflows.