Software Engineer, Algorithms Team

4M Analytics · telaviv

Description Software Engineer, Algorithms Team 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. At the core of this mission is a computer-vision engine that detects and localizes utility infrastructure from millions of diverse types of images. That engine only creates value if it runs reliably at scale — and that is where this role lives. We are looking for a builder: an engineer who is genuinely energized by the challenge of making complex systems work, who plans like an architect, debugs relentlessly, and learns whatever the problem demands. The Opportunity We are looking for a Software Engineer to join our core Algorithm team as an dedicated data-core / platform engineer. You will support the algorithm engineers developing detection algorithms to design and build the infrastructure they run on: the object-detection (OD) pipeline, its orchestration and deployment, its data and model catalog, and the benchmark and labeling systems that drive model improvement. This is a high-autonomy role with real, end-to-end ownership of production systems from day one. The technologies listed in this description are examples of our day-to-day — not a rigid checklist. We care far more about how you think, how you plan, how you debug, and how fast you learn than about which specific tools you have already used. If you love the craft of making things work and want to go deep, you can learn the rest here. In the AI era, being a strong engineer means more than writing great code. It means operating as an architect who directs AI agents — designing the solution with clarity, then guiding them 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. What You'll Do Take on hard, open-ended infrastructure challenges and make them work — designing, building, decoupling, and hardening the systems behind our object-detection pipeline, from data and model management to benchmarking, so everything runs reliably at scale. Architect and build the backbone of the OD pipeline — orchestration (Airflow on Kubernetes), data plumbing (S3 / PostGIS / SQS), CI/CD, and deployment across multiple environments — designing clean interfaces and data contracts the algorithm team can build on with confidence. Debug across the whole stack, wherever the problem leads — a stuck DAG, a flaky pipeline stage, a slow query, a GPU/driver mismatch — and turn one-off firefights into lasting fixes and better observability. Own the data and model lifecycle: versioned datasets and model weights with clear provenance, and the labeling → export → retraining loop that keeps the models improving. Learn fast and go deep. Pick up new tools and new layers of the stack as the work requires, and raise the team's engineering and operational standards as you go. Partner closely with algorithm engineers and the data-collection / labeling operations team to turn research prototypes into robust, scalable production systems. Integrate AI tools into your workflow and grow into operating as an architect who directs AI agents — designing the solution, then guiding them to build it. Who You Are This is what matters most to us: You love the challenge of building. You're energized by taking something messy, broken, or undefined and turning it into a system that runs reliably. You get real satisfaction from making things work. You're an architect by nature. You think in systems, plan before you build, and design clean boundaries and interfaces rather than bolting things on. You're a strong debugger. You're methodical and curious, and you enjoy chasing a problem through every layer — code, data, infrastructure, hardware — until you find the root cause. You're eager to learn. You don't need to already know our whole stack. You need to be the kind of person who masters new things quickly and genuinely enjoys doing so. Requirements Required Qualifications B.Sc. in CS, EE, or a related field, with 4+ years of professional software engineering experience. Strong Python and software-engineering fundamentals, with a high bar for clean, production-grade, well-tested code — whether you write it by hand or direct AI agents to produce it (our stack is Python 3.13). Real experience building and operating production systems end-to-end (backend, data, platform, or infrastructure) — not just shipping features on top of someone else's system. Comfort with cloud infrastructure and relational databases (we use AWS and PostgreSQL/P

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