Staff Algorithm Engineer

The 4M story is likely one you haven’t heard before: We are on a mission to reveal the world below us—to do for the world below ground what Google Maps did for the world above. By leveraging cutting-edge technology, we are mapping the subsurface infrastructure to make reliable, real-time utility data accessible to the construction industry - completely transforming a traditional industry. We’re a growing startup with 100 employees currently based in Tel Aviv, Israel, and Austin, Texas.

The Opportunity



We are looking for a Staff Algorithm Engineer to join our core Algorithm team — a high-autonomy group responsible for the algorithm and ML systems at the heart of 4M's mapping engine. This is a role for engineers who think in systems, bring cutting-edge computer vision and algorithmic thinking to ambitious real-world challenges, and own problems end-to-end with an entrepreneurial drive.

In the AI era, being a strong engineer means more than writing great code. It means operating as both an architect and a team lead — designing the solution with clarity, then guiding AI agents to execute it at a level and speed that wasn't possible before. We are building a culture where this is the norm, and we're looking for someone who is excited to work and grow in that direction.

You will work across computer vision and algorithm disciplines — researching solutions, designing experiments, and delivering production-grade implementations — while collaborating closely with data engineering and product teams.

What You'll Do



• Research and implement novel computer vision and algorithmic solutions for challenging real-world problems — spanning perception, learning, optimization, and graph-based reasoning.
• Own algorithm quality end-to-end: design experiments, evaluate results, and drive iterations until production reliability targets are met.
• Work across disciplines — sharing models, methods, and insights with algorithm, data engineering, and product teams.
• Monitor production model health proactively; identify degradation early and lead remediation efforts.
• Integrate AI tools into your workflow and grow into the role of architect and team lead — designing the solution, then directing agents to build it.
• Raise the bar on the team's technical culture through code reviews, knowledge-sharing, and rigorous algorithmic thinking.
  
  

• Relevant B.Sc./M.Sc. with 10+ years of experience as a Computer Vision or Algorithm Engineer, OR relevant Ph.D. with 7+ years of relevant industry experience.
• Broad and deep computer vision background, with strong algorithmic foundations — comfortable working across CV and adjacent algorithm domains.
• Deep proficiency in deep learning frameworks (PyTorch preferred).
• Proficiency in Python — writes clean, production-grade code.
• Proven E2E ownership: has taken CV problems from research to production, not just model experimentation.
• Strong problem-solving skills — comfortable with ambiguous, non-textbook problems.
• Self-motivated and entrepreneurial: identifies gaps, drives solutions, and takes accountability for outcomes.
• Mentor and upskill team members, including knowledge sharing and strategic technical development.
• Good communication skills — can clearly explain complex algorithmic decisions to both technical and non-technical stakeholders.
  
  

• You're already experimenting with AI tools in your work — code assistants, LLMs, or AI-augmented workflows — and you want to go further.
• You're open to learning how to operate as both an architect and a team lead: holding a clear picture of the solution, then directing AI agents to get there.
• You see AI not as a threat to engineering craft, but as a multiplier of it.
  
  

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

• Hard, original problems spanning computer vision and algorithm design that push the field forward. No textbook solutions, no incremental improvements on existing products.
• CV and algorithms are the core technology driving 4M's mission — your work is the product.
• Full end-to-end ownership: from research spike to production, you see the full impact of your work.
• You'll grow into operating as both architect and team lead — a scope of influence that compounds over time in ways traditional engineering roles don't offer.
• High-autonomy culture that trusts engineers to lead — real responsibility from day one, no micromanagement.
• Pre-scale startup (~100 people): your influence on the technical culture, the stack, and the direction is real and lasting.