Machine Learning Engineer

A highly successful Automotive Cybersecurity startup is defining the security standards for the era of the Connected Car.

Working with the world’s largest vehicle manufacturers (OEMs), the company develops advanced protection layers that secure smart vehicles against evolving cyber threats.

Backed by significant late-stage funding, the organization offers a high-impact environment at the intersection of Big Data, Cybersecurity, and AI.

The company is located in Central Israel (train-accessible) and operates a hybrid work model with two days of remote flexibility.

Role Overview:

• Scale & Performance: Joining the specialized Data Science & Data Engineering group to ensure complex models run efficiently at a massive scale.
• Core Product Innovation: Taking a lead role in bridging the gap between algorithmic research and production-grade software at the heart of the product's core engine.
• Algorithm Optimization: Working closely with Data Scientists to implement and optimize high-performance logic that processes vast streams of real-world automotive data.
• Data Infrastructure: Designing and maintaining robust data pipelines using cutting-edge Big Data and tabular processing tools.
• Technical Ownership: Driving the engineering lifecycle of ML models, from initial design and performance tuning to full-scale deployment in a distributed environment.

Requirements:

• B.Sc. in Computer Science or a related technical field – Mandatory.
• 5+ years of professional experience as an ML Engineer or in a similar high-scale engineering role – Mandatory.
• Expert-level proficiency in Python – Mandatory.
• Proven hands-on experience with Big Data tools (e.g., Spark/PySpark, Dask, Trino) – Mandatory.
• Strong experience with modern tabular data tooling (e.g., Polars, DuckDB, PyArrow) – Mandatory.
• Deep understanding of high-performance computing, distributed systems, and data processing architectures.
• Experience in the Cybersecurity or Automotive sectors – Significant Advantage.
• Ability to solve deep technical challenges within a fast-paced, innovation-driven environment.