Software Engineer (ML Team)

We are an established, fast-growing global InsurTech company operating at the intersection of data science, risk management, and cybersecurity.

We build enterprise-grade platforms that help businesses worldwide predict, monitor, and mitigate digital risks. Backed by top-tier venture capital funds, our R&D center in Tel Aviv drives the core technology, data pipelines, and machine learning models that power our predictive capabilities and automated decision-making systems.

About the Role

We are looking for a Software Engineer specializing in Machine Learning someone whose core strength is writing excellent, production-grade code.

In this role, you will own the engineering quality of our ML systems.

You will build, maintain, and monitor the services that run our models in production, while collaborating closely with data scientists to help them ship readable, maintainable, and resilient code.

Responsibilities

• ML Deployment & Scaling: Transition ML workloads from research to production, ensuring scalability, efficiency, and reliability.
• System Design: Design, build, and maintain ML services, infrastructure, and monitoring across their entire lifecycle.
• Cross-Team Collaboration: Integrate ML into our production systems, working closely with Core Engineering and DevOps teams.
• Data Infrastructure: Own the data infrastructure and tooling that our ML systems rely on, shaping unstructured data into analysis-ready formats.
• Engineering Excellence: Help data scientists write clean, maintainable code, and raise software engineering standards across the team.

Qualifications

• 4+ years of experience as a Software Engineer, with proven hands-on experience in the ML domain.
• Strong Python fundamentals, OOP, design patterns, SOLID principles, clean code, and robust architecture.
• Solid grasp of core ML concepts (e.g., linear regression) you deeply understand the models you put into production.
• Experience building services and tools that track the ML lifecycle and optimize ML workloads.
• Working knowledge of data cleaning, data wrangling, and utilizing the right tools for the job.
• Practical experience with AWS (specifically EKS).
• Driven, results-oriented, and a self-starter.
• A solid track record of execution with strong attention to detail.
• Bachelor's degree or higher in Computer Science or another STEM field.

Nice to Have

• Experience integrating MLOps tooling (experiment trackers, data versioning, and CI/CD/CT practices).
• Hands-on Ops experience with AWS and Kubernetes.
• Background or exposure to Data Science, particularly in deploying and maintaining models.