לוח משרות דרושים Deep learning researcher

looking for a highly motivated Algorithm Intern to join our cutting-edge AI team. This is a unique opportunity to work on real-world deep learning challenges, contribute to production-level systems, and collaborate with top-tier engineers and researchers.
This is a full-time, 3-month internship, with the potential to transition into a full-time Algorithm Engineer position upon successful completion.
Why Join Us?
Work on cutting-edge AI technology used by real users
Learn fast and gain real production experience
Be part of a collaborative, high-impact team
Opportunity to convert to a full-time role
Responsibilities
Design, implement, and improve deep learning models.
Work on real-world AI problems using large-scale data.
Collaborate closely with experienced engineers and researchers.
Run experiments, analyze results, and optimize model performance.
Take ownership of projects and drive them forward independently.
Stay up to date with the latest trends in AI and deep learning.

We arelooking 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.

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.

Required Senior Deep Learning Algorithm Researcher - Air2Road Localization
Description
Backed by over 250 patents and trusted by global industry leaders including Toyota and BMW, we are redefining AI for the future of autonomous driving.
Our breakthrough Air2Road Localization technology fuses aerial imagery with real-time ground view data to achieve accurate vehicle localization, even in areas where GPS fails. Join our Air2Road team to shape the next generation of AI-driven localization, tackle cutting-edge research challenges, and turn state-of-the-art deep learning into real-world impact!
Responsibilities
As a senior member of the Air2Road algorithm team, you will:
Research, design, and implement state-of-the-art deep learning models in computer vision (e.g., detection, segmentation, transformers, self-supervised learning).
Use classical computer vision algorithms together with deep learning to build robust solutions.
Translate research into production-ready algorithms, writing clean, efficient, and scalable code in Pytorch.
Explore creative ideas, experiment with novel architectures, and continuously push beyond current SOTA.
Take ownership of your work end-to-end, from concept through prototyping to deployment in production.

Required Senior Algorithm Engineer
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.

Required Deep Learning Algorithm Developer - ADAS group
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 provide systems capable of operating in various environments: On mainline and high-speed rail, in urban environments, and in challenging switchyards. we offer a range of complementary features based on collected and analyzed data: Image-based Navigation, GIS Mapping and Predictive Maintenance.
Were 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 team is looking for a Deep Learning Engineer.
We are one of the few companies to have trained multi-billion parameter Large Language Models (LLMs), a feat that involves the most advanced engineering (large scale distributed training on thousands of cores). Serving these LLMs efficiently requires cutting-edge technology as well. As a deep learning engineer on the team, you will be responsible for maintaining and improving our training infrastructure, developing/scaling/testing new ideas, and adapting our code to run on and best utilize the newest and most advanced hardware accelerators.
Role and Responsibilities
Develop Large Language Models as part of our applied research projects and in support of our Platform, including designing, implementing and training massive-scale deep language models
Implement, optimize, scale and test new cutting edge ideas and architectures
Perform large-scale evaluations and comparisons of trained models across a range of benchmarks, as well as adding support for new benchmarks

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.

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.

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 a AI Architect.
Responsibilities
1. AI Architecture & Technical Leadership
Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

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.