Data & ML Engineer

Mobileye’s Hawkeye team develops advanced close-range 3D perception technology for autonomous vehicles, enabling safe automated parking and low-speed maneuvers in challenging environments. We build multi-camera deep learning systems to provide precise and reliable understanding of the vehicle’s surroundings.

We are looking for a Data & ML Engineer to develop and optimize the data infrastructure supporting our deep learning models. In this role, you will build scalable pipelines and tools for processing images, videos, and geometric data, as well as evaluating model outputs. Working closely with deep learning researchers, you will improve system performance, reduce computational costs, and accelerate development and training cycles.

What will your job look like:

• Develop and optimize distributed data processing and evaluation pipelines, focusing on memory efficiency, throughput, and performance.
• Build tools for data exploration, manipulation, validation, and quality assessment.
• Collaborate with deep learning researchers, infrastructure and data teams, and internal stakeholders to define data requirements and improve workflows.

All you need is:

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Statistics, or a related field from a leading university.
• 2+ years of hands-on experience in software or data engineering.
• Excellent Python and Linux skills, with strong software engineering fundamentals.
• Hands-on experience with SQL, Spark, and PyArrow.
• Experience optimizing distributed data pipelines or compute-intensive systems for memory efficiency and parallel execution.
• Familiarity with PyTorch and ML workflows, including datasets, training, checkpoints, model evaluation, and GPU computation.
• Strong ownership, independent problem-solving skills, and ability to collaborate across teams.

Nice to have:

• Master's degree in a relevant field.
• Experience in computer vision or autonomous driving systems.
• Familiarity with model deployment, hardware-aware ML, or specialized AI accelerators.
• Experience using Generative AI models for data labeling and inference.