Principal Software Engineer

Role overview

Build and operate the machine learning platform behind identity products, enabling teams to train, evaluate, deploy, and monitor models used for real-time decisions at large scale. The work spans data infrastructure, software engineering, and MLOps, with a focus on dependable feature pipelines and low-latency model serving.

Responsibilities

- Design and run scalable tools and services for model promotion, evaluation, deployment, and production monitoring. - Develop feature-store capabilities that support reuse, governance, lineage, and consistency between offline training and online serving. - Build streaming feature pipelines and real-time model-serving systems for latency-sensitive production use. - Automate data workflows for training, inference, and analytics using Python, SQL, and distributed processing tools. - Own model delivery practices such as CI/CD, containerized deployment, monitoring, and lifecycle management. - Create utilities that improve the efficiency of model training and deployment for data scientists and engineers.

Requirements

- At least six years building ML platforms, data infrastructure, and large-scale distributed systems. - Expert programming ability in Python and SQL; Java is an advantage. - Hands-on experience with Spark or a comparable distributed computing framework. - Production experience with Airflow, MLflow, Kubernetes, and CI/CD pipelines. - Experience with offline and online feature stores, streaming systems such as Kafka or Flink, and low-latency model serving. - Public cloud experience, preferably AWS, including managed data or machine learning services; strong problem-solving and cross-team communication skills.

Nice to have

- Experience with lakehouse and data platform tools such as Apache Iceberg, dbt, or OpenMetadata, including data governance and lineage. - Experience operating self-service ML infrastructure across multiple cloud accounts. - Familiarity with deep learning, large language models, reinforcement learning, or PyTorch; a master’s degree in an applied science field.

Benefits and work setup

The source describes a hybrid arrangement in Tel Aviv. Listed benefits include paid time off and holidays, parental leave, healthcare options, retirement programs, education reimbursement, and a commuter offset in some locations.