Machine Learning Engineer

A well-established Automotive-Tech company is redefining vehicle security and data analytics for the connected car era.

Backed by hundreds of millions of dollars in total funding from major strategic global investors, the company provides a critical cloud-based platform for international car manufacturers, insurance providers, and fleet managers.

The company is located in Central Israel (short walking distance from the train station) and operates a hybrid work model with two days of remote flexibility.

Role Overview:

• Solo MLE Pillar: Serving as the dedicated Machine Learning Engineering expert within the Data Science group, responsible for bridging the gap between research and high-scale production.
• Production Scaling: Building and scaling ML solutions for massive tabular datasets, focusing on vehicle health and cybersecurity products.
• Engineering Standards: Defining the technical standards that enable the Data Science team to operate at scale, ensuring system reliability and performance.
• High-Performance Infrastructure: Working with massive data streams under strict latency, CPU, and memory constraints.
• End-to-End Ownership: Leading the lifecycle of key features, from data profiling and optimization to model serving and monitoring.

Requirements:

• Extensive professional experience as an ML Engineer or Software Engineer (ML focus) – Mandatory.
• B.Sc. in Computer Science or a related technical field – Mandatory.
• Proven track record of deploying and maintaining End-to-End ML environments in Production – Mandatory.
• Expert-level Python skills (Clean Code, Architecture, Testing) – Mandatory.
• Strong Systems Thinking with hands-on experience in Profiling and Optimization – Mandatory.
• Significant experience with Distributed Processing (e.g., Spark, PySpark, Dask, or Trino) – Mandatory.
• Experience with modern Tabular tools (e.g., Polars, DuckDB, PyArrow) – Mandatory.
• Hands-on experience with Tabular ML in Production (EDA, Feature Engineering, Tuning) – Mandatory.