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Mobileye
Open roleUpdated

Senior Data & ML Infrastructure Engineer

MobileyeRamat Gan, Israel
Work model
Hybrid
Experience
5+ years
Employment
Full Time
Compensation
Not disclosed
Technology signal
10 tags

Technology context

10

Parsed from the vacancy text; ordered by relevance to this role.

AIMachine LearningDeep LearningPythonPyTorchComputer VisionDevOpsSparkLinuxSQL

Full listing

Role description

Join METRO, the team developing the deep-learning backbone at the heart of Mobileye's autonomous-driving perception system. Our work powers advanced, large-scale multi-task models.

We are looking for an ML Data Engineer to own the engineering foundations behind its development and training. At petabyte scale and hundreds of thousands of daily jobs, you will build pipelines and tools that process images, video, geometric information, and model outputs. Working alongside deep-learning researchers, you will eliminate resource-intensive bottlenecks and reduce computation costs and iteration time.

What will your job look like?

  • Optimize distributed data and evaluation pipelines for memory efficiency, throughput, and training performance.
  • Build tools for data exploration, manipulation, validation, and quality assessment.
  • Own model manipulation, packaging, distribution workflows, and interfaces with downstream deployment and EyeQ integration.
  • Coordinate data contracts and workflows with researchers, infrastructure and data teams, and internal customers across Mobileye.

All you need is

  • Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field from a leading university.
  • 4+ years of hands-on software or data-engineering experience.
  • Excellent Python and Linux skills with strong software-engineering foundations.
  • Strong experience with SQL, Spark, and PyArrow.
  • Experience optimizing distributed pipelines or compute-intensive systems for memory use and parallel execution.
  • Familiarity with PyTorch and ML workflows, including datasets, training, checkpoints, evaluation, and GPU computation.
  • Strong ownership, independent problem-solving, and cross-team collaboration skills.

Advantages

  • 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.