Senior Algorithm Engineer

Who We Are

4M Analytics is building the first Subsurface World Model: an AI platform that uses visual reasoning and large-scale data fusion to turn the undocumented world beneath our streets into one living, intelligent map. We make reliable utility data accessible to the construction industry, government agencies, and utility owners, and we are changing how infrastructure is understood and protected.

We are Series C, backed by Insight Partners, Viola, and F2, with 120 people across Tel Aviv and Austin, Texas. The problem is massive, the momentum is real, and we are moving fast.

The Opportunity

We are looking for a Senior 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.
  
  

• Relevant B.Sc./M.Sc. with 7+ years of industry experience as a Computer Vision or Algorithm Engineer, OR relevant Ph.D. with 4+ 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.
• 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.
• High-autonomy culture that trusts engineers to lead — real responsibility from day one, no micromanagement.
• Pre-scale startup: your influence on the technical culture, the stack, and the direction is real and lasting.