4M Analytics

Description 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 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. • 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 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. 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.

Description Who We Are: The 4M story is likely one you haven’t heard before: We are on a mission to unlock access to 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 As a Senior DevOps Engineer, you will be a key member of a high-performing team focused on building resilient, highly available, and production infrastructures. Your role is to bridge the gap between development and operations by applying software engineering principles to automate, scale, and optimize our cloud ecosystem. Utilizing Terraform for lifecycle management and Amazon EKS for orchestration, you will build and scale robust, self-healing environments. We are looking for an engineer who doesn't just use tools, but understands the Linux foundation they run on. You will work to ensure our systems are transparent, measurable, and elastic through reliable GitOps practices and full-stack observability. You will also implement and maintain essential DevSecOps tools to keep our environments secure. Key Responsibilities • Linux Systems Engineering: Maintain a deep-dive understanding of Linux internals to identify bottlenecks and optimize configurations. • Container Orchestration: Manage production-grade Amazon EKS clusters and implement modern autoscaling solutions like Karpenter. • Full-Stack Observability: Own the migration and maintenance of the Grafana-based observability suite (Grafana, Tempo, Mimir, Loki). • GitOps & IaC: Lead GitOps initiatives with ArgoCD and architect modular Terraform or Crossplane codebases. • Python Tooling: Develop custom tools and AI agents using Python to automate research and development cycles. • Vulnerability Management: Integrate automated image scanning and Software Composition Analysis (SCA) tools into the SDLC. Requirements Required Qualifications • 7+ years of hands-on experience with a cloud provider, preferably AWS. • Strong experience with Infrastructure as Code (IaC) using Terraform. • Deep understanding of Kubernetes (EKS), including architecture, networking, and troubleshooting. • Solid Linux system administration skills. • Proficiency in Python or similar for writing production-grade code and tools. 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. This means you are experimenting with AI tools (code assistants, LLMs) and see AI as a multiplier of engineering craft. Preferred Qualifications • Experience with Crossplane for cloud-native infrastructure management • Familiarity with DevSecOps practices and security orchestration (policy enforcement, scanning, shift-left security) • Understanding of observability concepts, including hands-on experience with Prometheus, Grafana, and Loki • Experience with Argo CD and GitOps-based deployment workflows

Description Who We Are  The 4M story is likely one you haven’t heard before: We are on a mission to unlock access to 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 120 employees currently based in Tel Aviv, Israel, and Austin, Texas. The Opportunity We're seeking an experienced Software Engineer with a strong background to become an integral member of our Data-Core team, tasked with the mission of processing, structuring, and analyzing hundreds of millions of data sources. Your role will be pivotal in creating a unified, up-to-date, and accurate utilities map, services, and applications for accelerating our mapping operations. Your contributions will directly impact our core product's success. Responsibilities • Collaborate with cross-functional teams to design, build, and maintain data processing pipelines while contributing to our common codebase. • Contribute to designing and implementing data architecture, ensuring effective data storage and retrieval. • Develop and optimize complex Python-based applications and services to allow more efficient data processing and orchestration, enhancing the quality and accuracy of our datasets. • Drive the scalability and performance optimization of data systems, addressing infrastructure challenges as data volume and complexity grow. • Create and manage data infrastructure components, including ETL workflows, databases, supporting seamless data flow and accessibility. • Design and implement CI/CD processes for data processing, model training, releasing, testing and monitoring, ensuring robustness and consistency. • Implement geospatial data processing techniques and contribute to the creation of our unified utilities map, enhancing the product's geospatial features. Requirements • Bachelor's degree in Computer Science, Engineering, or related field. • 4+ years of experience in software engineering with a focus on data systems. • Proficiency in Python. • Experience with big data technologies like Hadoop, Spark, or Kafka. • Strong problem-solving skills and attention to detail. • Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.

Description 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.