🕒 3 days ago
Build and improve production machine learning systems, developing scalable data pipelines, deep learning and time-series models, agentic workflows, and monitoring processes for model performance.
Deep Learning Algorithm Developer - Ground Truth
🕒 3 days ago
Deep LearningComputer VisionMachine LearningNeural Networks
📜 Description
- Own deep learning projects, from defining product requirements and designing solutions to overseeing execution.
- Develop new models and improve the performance of existing algorithms.
- Collaborate with cross-functional teams to understand requirements and deliver solutions.
- Research advances in deep learning, multi-task learning, and AI architectures and apply them to algorithms.
- Build offline models for sensing the world around vehicles.
🛠️ Requirements
- B.Sc. in Mathematics, Physics, Computer Science, or Electrical Engineering, with 3+ years of experience as an algorithms, deep learning, or machine learning developer.
- M.Sc. or Ph.D. research in computer vision, deep learning, or machine learning.
- Strong theoretical and practical background in computer vision, machine learning, and deep learning.
- Experience implementing end-to-end deep learning pipelines, including data preparation, training, validation, and deployment.
- Proficiency with PyTorch or other deep learning frameworks.
- Proficiency in Python.
✨ Benefits
- Design, develop, and implement deep learning algorithms for computer vision problems.
Full job description
You will join a collaborative team dedicated to researching and developing advanced neural networks critical to Mobileye’s key products, focusing on 2D and 3D vision technologies.
You will be responsible for the full cycle of deep learning R&D, modeling new solutions and enhancing the performance of existing ones, while participating in innovative, cross-organizational initiatives.
This position offers the opportunity to be part of a fast-paced and forward-thinking environment, working on cutting-edge technology and SOTA models aimed at creating the best possible offline models for sensing the world around the vehicle.
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