Ramat Gan
Full time
About us:
Mobileye is a global leader in Physical AI, developing computer vision, software, and hardware to power autonomous driving solutions and humanoid robots. Our mission is to bring autonomy into the real world by building intelligent technologies that are designed to expand accessibility and enhance everyday life, from advanced driver assistance systems (ADAS) and autonomous driving to robotics and humanoids.
Built on decades of automotive innovation and industrial-scale AI expertise, Mobileye technologies power more than 230 million vehicles worldwide. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for the real world.
About the team:
We are looking for a Senior ML Algorithm Engineer to lead the development and optimization of machine learning models for challenging real-world problems. In this role, you will work hands-on across the full model-development lifecycle: understanding the task, designing and adapting algorithms, building effective training strategies, analyzing data and failure modes, and improving model quality and efficiency through rigorous experimentation. This is an algorithm-focused role for someone who enjoys getting deeply involved in the details of model training and optimization. You will not simply operate an existing training infrastructure—you will investigate open-ended problems and develop practical solutions involving model architecture, data and sample selection, training objectives, optimization methods, and evaluation
What will your job look like:
- Work on the semantics of road objects, using harvested tabular data as the primary input to our algorithms — turning large-scale, real-world observations into models that capture object meaning, attributes, and behavior on the road network.
- Design, implement, and optimize machine learning and deep learning algorithms for these semantic tasks, from architecture and training objectives through evaluation and efficiency.
- Develop and improve end-to-end model training pipelines, from data preparation and sampling of harvested tabular datasets through training and evaluation.
- Investigate model behavior, identify failure modes, and drive targeted algorithmic improvements.
- Develop effective strategies for data selection, dataset composition, sampling, augmentation, loss design, and training schedules.
- Lead the investigation of complex algorithmic challenges, uncover patterns in data and model behavior, and translate insights into measurable improvements.
All you need is:
- 5+ years of experience in algorithm engineering using machine learning, deep learning, or neural networks.
- Strong hands-on experience designing, training, evaluating, and optimizing.
- Strong programming skills in Python.
- Hands on experience with Spark, Pandas, Pytorch and AWS.
- Experience with Polars and DuckDB- an advantage
- Experience with some of the following: sampling strategies, data augmentation, hyperparameter optimization
- Strong understanding of distributed systems, scalability, and performance optimization.
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Ability to independently investigate complex problems, identify patterns in data and model behavior, run experiments, and translate findings into measurable algorithmic improvements.
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Strong analytical and problem-solving skills, with a practical, hands-on, and ownership-driven mindset.
Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!
