דרושים » תוכנה » Deep Learning Engineer

Were looking for a Deep Learning Algorithm Engineer to join a cutting-edge team driving R&D innovation in signal processing and radar-based systems. In this role, you will lead the end-to-end development of deep learning models, from data strategy and model training to deployment in real-world defense applications.
Responsibilities include:
Design and implement state-of-the-art DL algorithms for diverse data formats, including 2D spectral representations, 3D point clouds etc.
Develop scalable pipelines for training, evaluation, data labeling and preprocessing
Train and optimize models using frameworks like PyTorch/TensorFlow
Conduct literature reviews and stay on top of the latest AI trends
Prepare models for integration and deployment in production environments.

Were looking for a Deep Learning Algorithm Engineer to join a cutting-edge team driving R&D innovation in signal processing and radar-based systems. In this role, you will lead the end-to-end development of deep learning models, from data strategy and model training to deployment in real-world defense applications.
Responsibilities include:
Design and implement state-of-the-art DL algorithms for diverse data formats, including 2D spectral representations, 3D point clouds etc.
Develop scalable pipelines for training, evaluation, data labeling and preprocessing
Train and optimize models using frameworks like PyTorch/TensorFlow
Conduct literature reviews and stay on top of the latest AI trends
Prepare models for integration and deployment in production environments.

We are looking for an experienced Deep Learning & AI Infrastructure Engineer to join our AI team. In this role, you will develop and deploy advanced deep learning models for signal processing and build the infrastructure and tooling required to scale AI training and inference in both research and production environments.
You will be responsible for the end-to-end lifecycle of AI workloads, including data ingestion and preprocessing pipelines, model training infrastructure, efficient inference systems, and automated experiment tracking.
Key Responsibilities
Design, implement, and optimize deep learning models and pipelines for signal and image analysis.
Build and maintain AI infrastructure components to support model training, versioning, monitoring, and deployment.
Develop scalable data processing pipelines for datasets, including ingestion, labeling, augmentation, and preprocessing at scale.
Implement automated training workflows using tools such as ClearML or other experiment tracking platforms, ensuring reproducibility and model governance.
Collaborate with system engineers to integrate AI models into real-time radar systems and ensure efficient inference performance.
Optimize distributed training and resource utilization.
Run performance tuning, testing, and benchmarking for both training and inference workloads.
Document infrastructure components, training procedures, and model lifecycle processes.

Required Deep Learning Algorithm Developer - ADAS group
Description
As part of the algorithm team for the next generation of autonomous driving, you will:
Responsibilities
Understand deeply, implement, train, and evaluate recent state-of-the-art algorithms in computer vision (e.g., object detection, semantic segmentation, self-supervised learning, vision transformers) for various domains.
Adapt algorithms into robust and scalable production-ready algorithms. Write clean and efficient code, ensuring compatibility with existing systems and frameworks, and real-time needs. Take full responsibility for your algorithms end-to-end until deployment on the edge device for production.
Develop and implement new computer vision algorithms (architectures, loss functions, post-processing, training, and evaluation methods) that surpass SOTA algorithms and achieve desired performance levels in our domain.

We are looking for an Algorithm Researcher to join our team in Israel and help build the next generation of AI-driven financial crime detection.
In this role, you will work at the intersection of research, mathematics, and advanced AI, turning complex theoretical concepts into scalable, production-ready algorithms. You will solve high-dimensional real-world problems and contribute directly to mission-critical systems used by leading financial institutions worldwide.
Technology: Python, NumPy, SciPy, Pandas, PyTorch / TensorFlow, LLMs, RAG, vector databases, large-scale data processing
What youll work on:
Designing and developing advanced algorithms for complex financial crime detection challenges
Translating mathematical models and research concepts into scalable production systems
Building and optimizing ML and LLM-based solutions for real-world deployment
Working with transformers, attention mechanisms, sequence modeling, and representation learning
Developing solutions using RAG, embedding models, vector databases, and generative AI evaluation frameworks
Designing AI agents, tool-using LLM architectures, and autonomous decision-making pipelines
Improving model accuracy, robustness, explainability, and inference efficiency
Collaborating with engineers, data scientists, and domain experts to bring research into production.

We are global leader in autonomous vehicle (av) technology. if youre an experienced deep learning Developer driven by a passion to shape the future of mobility, join us to make av a reality. the 3d perception team builds transformer-based vision models trained on large-scale driving video for the next generation of autonomous vehicles. our end-to-end temporal network fuses multi-view cameras into a unified 3d sensing state that powers planning.
what will your job look like?
develop, implement and optimize state-of-the-art transformer-based temporal vision models
extend network capabilities, analyze results and errors, and deliver measurable improvements to the driving scene understanding
work shoulder-to-shoulder in a large, collaborative group
research and integrate the latest advancements in 3d detection and perception
improve algorithmic performance through rigorous experimentation and innovation
work with large-scale datasets
research new advances in the field from the literature and industry.

the road algorithm team is responsible for one of the most critical and challenging tasks in autonomous driving - detecting and understanding the drivable road. our work leverages deep neural networks and geometric modeling to deliver reliable and high-quality road perception for autonomous vehicles.
we are looking for an expert deep learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities. what will your job look like:
conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
lead exploratory investigations into new architectures, training strategies, and data utilization methods
join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
own projects end-to-end - from concept and experimentation to integration and scalable deployment

Rail Vision is a multidisciplinary startup headquartered in Ra'anana. We are the leading provider of obstacle detection, collision avoidance and drive able areas systems in the railway industry around the globe, supporting Autonomous Train Operations. With our unique cognitive sensor fusion technology, based on advanced electro-optic sensors and perception solution, Rail Vision systems detect obstacles on and along the tracks from up to 2 kilometers away, in real-time, and in diverse weather and lighting conditions. We provide systems capable of operating in various environments: On mainline and high-speed rail, in urban environments, and in challenging switchyards. Rail Vision offers a range of complementary features based on collected and analyzed data: Image-based Navigation, GIS Mapping and Predictive Maintenance. We’re looking for a brilliant Deep learning research engineer to join our Algorithms group. What will you do?
* Be a researcher of the core deep learning algorithms and communicate with other researchers.
* Design and implement advanced algorithms to solve complex problems.
* Developing the next generation algorithms including different CNN architectures, CV algorithms and algorithms that utilize Physics in complex environment.

our imaging radar department develops high-performance 4d imaging radar systems for autonomously driving vehicles. the phy algo group is leading the innovative research and the development of the entire algo processing pipeline starting from the iq samples and up to object detection. the group is responsible for the entire radar simulation, including novel waveform design, transceivers, environment, and the radar signal processing pipeline. the group is also leading the phy architecture and developing ai based signal processing. what will your job look like?
research, develop and implement signal processing algorithms.
solve applied radar processing problems.
develop radar and environment simulations for verification of algorithm pipes at the system level.
develop ai based algorithms for radar signal processing. including developing the training and testing environments for these algorithms.
analyze field recorded data and confirm system performance through simulations.

We are the world leader in automotive and driving assistance systems, developing the world's most advanced software technologies and hardware architectures.
our group is located in haifa and is responsible for enabling the deep learning and computer vision algorithms on the platform. the technology we develop enables state-of-the-art deep neural networks to run efficiently in vehicles - contributing to saving lives and enabling autonomous vehicles. this is an exciting opportunity to work with highly talented engineers and be a part of a product with a lot of innovation and work on cutting-edge compiler and optimization technologies in the ai domain.
what will your job look like?
shape our product by applying cutting-edge deep learning network optimization techniques and will have the chance to influence future generations of our hardware and software
develop a deep learning compiler stack that takes neural network descriptions created in frameworks such as tensorflow and pytorch and converts them into code suitable for execution on custom-built our hardware
use state-of-the-art open-source technologies such as mlir and work closely with the open-source community
develop optimized implementations of a variety of neural-network operations and new optimization techniques and algorithms to efficiently map ml models onto our state-of-the-art systems
develop a toolchain that will provide a quantum leap in deep learning capabilities and performance.