לוח משרות דרושים Deep learning researcher משרה מלאה, לחיפוש זה נמצאו 24 משרות

Required Algorithm Researcher - Autonomous Driving (CTO Group)
The CTO Group is a small, elite team focused on the decision-making module of our autonomous driving system.
Our mission is to solve some of the hardest problems in autonomous driving by combining the full spectrum of modern computer science - from rigorous mathematical modeling, optimization, and algorithm design to deep learning.
The team develops the driving policies that translate system-wide inputs into safe, efficient, and human-like driving behavior. Our work spans classical algorithms, optimization under constraints, probabilistic reasoning, reinforcement & supervised learning, all grounded in real-world driving data.
The group is comprised of top researchers and developers and is led by world-class scientists, offering a unique opportunity to work closely with the CTO, shape the future of autonomous driving, and influence the company's technical direction.
What will your job look like:
Research and develop innovative algorithms for autonomous driving planning and decision-making.
Model complex real-world driving scenarios and formulate them as optimization, learning, or algorithmic problems.
Apply a broad range of techniques - from mathematical modeling and classical algorithms to machine learning and deep learning - to improve driving policies.
Analyze large-scale driving data to gain insights, validate hypotheses, and improve system robustness and performance.
Design and implement high-quality production-ready code in a research-driven environment.
Read, evaluate, and build upon state-of-the-art scientific literature in algorithms, AI, and machine learning.

We are looking for an exceptional Deep Learning Engineer to join our core autonomy team. In this role, you will be responsible for building the AI-driven "brain" of our autonomous driving technology. Your focus will be on designing, training, and deploying state-of-the-art Deep Learning models that handle high-level prediction and driving policy. You will solve complex, real-world challenges by leveraging advanced neural network architectures to optimize decision-making under high uncertainty.

Responsibilities:
Model Training & Architecture: Design, train, and optimize cutting-edge Deep Learning models for prediction and driving policy.
End-to-End DL Development: Take ownership of the full DL lifecycle, from data curation and feature engineering to training, evaluation, and deployment.
Scalable Infrastructure: Develop robust pipelines for training and evaluating models on massive, real-world driving datasets.
Production Deployment: Optimize and integrate deep learning models to run efficiently in real-time within the core autonomy software stack.
Full-time availability at our Tel Aviv HQ.

We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges.

A day in the life and how youll make an impact:

Design and Development of novel, robust and efficient Machine Learning/ Deep Learning algorithms for major Vision challenges.
Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems.
Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data-centric AI methodologies (active learning, data curation).
Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for real-time inference constraints (on Edge/Cloud devices).

Were looking for talented Senior Algorithm Engineer to help us develop innovative technologies for cancer diagnosis.
In this role, youll work on huge, unique datasets of high-resolution pathology images from leading institutes worldwide, develop and optimize algorithmic solutions for complex problems using cutting-edge technology, integrate your algorithms into our products and receive feedback from clinicians using them in live clinical settings, and work closely with our multi-disciplinary team of Machine Learning experts, experienced software developers and medical professionals.

we are looking for a deep learning engineer experienced with computer vision to join our DL algorithms Team. We are dealing with a variety of tasks such as regression, segmentation, classification and detection while editing millions of images every week for professionals, and holding tens of millions edited images by professionals used as datasets
Responsibilities:
Design, development and bring to production novel, robust and efficient deep learning algorithms in the field of computer vision.
Create proofs of concept for new products and technology.
Evaluate and benchmark different algorithms for unique, proprietary datasets.
Collaborate with team members to define future technology and features.

we are looking for a Senior Machine Learning Engineer.
As a Senior Machine Learning Engineer , you will play a crucial role in developing and implementing machine learning models that drive our products and user experiences. You will have a significant impact on our large and growing user base by leveraging the latest AI technologies to solve challenging problems at scale. This is a unique opportunity to join a forward-thinking team that is passionate about innovation, data, and machine learning.
What youll do:
Design, develop, and deploy machine learning models for various business needs.
Collaborate with cross-functional teams, product managers, and software engineers, to integrate ML solutions into production systems.
Experiment with and iterate on model architectures to improve accuracy, efficiency, and scalability.
Work with large datasets to preprocess, clean, and extract meaningful features for model training.
Utilize MLOps best practices to automate and streamline the development lifecycle of ML models.
Monitor model performance and fine-tune for optimization.
Stay updated with the latest research and advancements in machine learning and AI.