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Staff Algorithm Engineer

4M AnalyticsTel Aviv-Yafo, Tel Aviv District, IsraelNot specifiedFull-timeSeniority: Not specified

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Willbi insight

The role in plain words

Must-have
  • 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
  • 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
Nice-to-have
  • 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

Extracted from the job description · kept up to date automatically

Who this suits

Full job description

Original listing · kept for reference

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.

Requirements:

Required Qualifications

• 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.

AI-First Mindset

We are building an AI-first engineering culture, and we're looking for engineers who are genuinely excited about working this way. You don't need to arrive with a fully formed AI workflow — but you should have the curiosity and the drive to develop one.

In practice, this means:

• 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.

Specific tools and methods can be learned together. What matters is the mindset and the motivation to grow into this way of working.

Preferred Qualifications (not required!)

• 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.

Why Join 4M

If you want to apply cutting-edge computer vision and algorithmic thinking to ambitious, unsolved real-world problems — and see your work directly shape a product that is redefining an industry — this is that role!

• 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.

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