Senior Algorithm Engineer - Model Training & Optimization

About the Role

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. • Ability to independently investigate complex problems, identify patterns in data and model behavior, run experiments, and translate findings into measurable algorithmic improvements. • 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!

Workplace

• Ramat Gan