Phoenix Financial is a leading and innovative force in Israel’s insurance and financial services sector, driven by cutting‑edge technology and a commitment to delivering exceptional value.

We are looking for a Senior Machine Learning Engineer to take ownership of the production lifecycle of our pricing models - from infrastructure design through deployment, monitoring, and continuous improvement.

our ML Pricing team develops production-grade pricing engines that directly impact underwriting precision, growth, and profitability. Our models operate at scale and require robust infrastructure, reproducibility, and operational excellence.

What you’ll do?

• Design, build, and maintain end-to-end ML pipelines and ETLs (data extraction and processing, training, validation, packaging, deployment).
• Own model deployment processes, including containerization with Docker and scalable production setup.
• Operate within a Git-based CI/CD (GitOps) framework in close collaboration with DevOps.
• Ensure production stability, performance consistency, calibration integrity, and data/model drift detection.
• Otimize runtime performance and resource efficiency in production environments.
• Support research and development of pricing and risk models (supervised and unsupervised ML, segmentation, behavioral pricing, ranking models).
• Build scalable feature engineering pipelines for categorical, telematics, geographic, and behavioral data.
• Collaborate with actuaries, data scientists, and business stakeholders to translate pricing logic into robust ML systems.

What are we looking for?

• BSc or MSc in Computer Science, Engineering, or related quantitative field.
• 5+ years of experience deploying ML systems in production environments.
• Strong experience building and operating ML pipelines in AWS services.
• Hands-on expertise with Docker, Kubernetes, Git and CI/CD.
• Strong Python proficiency and experience with production-grade ML codebases.

Why join us?

• Join a team where you’ll shape real machine‑learning products end‑to‑end, owning models from research to production and seeing your work create immediate, measurable impact.
• Work in a highly technical environment with strong engineering standards, modern MLOps practices, and the freedom to experiment, innovate, and influence architectural decisions.
• Collaborate with top‑tier data scientists, engineers, and product leaders on complex challenges, with clear opportunities for growth, leadership, and driving ML strategy across the organization.

Full-time, Sunday-Thursday, 9 hours per day, hybrid

Rishon LeZion, The 1000 complex, adjacent to Moshe Dayan Railway