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Join our education-services team as a dynamic technical trainer and content developer. We're seeking an exceptional individual with expertise in networks, server administration, containerized environments, storage and orchestration tools to lead the delivery and development of technical content related to our AI infrastructure and software solutions. As a key member of our team, you'll collaborate with internal and external experts to design and deliver lab-based training that empowers customers and partners to manage and optimize accelerated computing solutions across diverse workloads, including deep learning, data science, and high-performance computing.

What youll be doing:

Training Delivery: Conduct engaging face-to-face and remote training sessions for our customers and partners, with flexibility for up to 25% travel.

Content Development: Craft cutting-edge training materials aligned with our innovative AI and data center technologies.

Collaboration: Work closely with domain experts to develop course proposals that meet market demands and customer needs.

Lab-Based Training: Design interactive lab exercises enriched with diagrams, videos, and hands-on experiences.

Instructor Support: Develop comprehensive instructor resources, certification criteria, and assessment materials.

Required Computational Math Scientist
Our team at the Huawei Smart Platforms Innovation Lab is looking for exceptional talent to join us and lead the development of next generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage and networking at large-scale. We aim to drive innovations and deliver software defined infrastructure to HPC/AI applications.
We are looking for outstanding candidates with hands-on experience in algorithm/software development. If you are a team player with excellent communication skills and motivation to revolutionize application performance, youre welcome to join our team!
What you will be doing:
Envision, design and develop advanced algorithms to enable utilization of state-of-the-art hardware for HPC/AI applications
Research and implement innovative computational methods for optimizing massively parallel HPC/AI applications
Utilize advanced mathematical concepts such as Uncertainty Quantification, Mixed Precision Computing and Sparsity to improve performance of math libraries
Identify computational bottlenecks to improve existing products and processes
Collaborate with partners from academy and industry to conduct state-of-the-art research
Develop AI/ML methods to accelerate traditional scientific computing (AI4S)
Enhance computational algorithms using advanced parallel programming models (e.g. OpenMP, MPI)
Contribute to open-source scientific computing libraries (e.g. OpenFOAM, PETSc).

The Industry Solutions Engineering (ISE) team is a global engineering organization that works directly with Microsofts most strategic Healthcare and Life Sciences customers who are looking to leverage the latest technologies to address their toughest challenges. We develop solutions side-by-side with our customers through collaborative innovation to solve their challenges. This work involves the development of broadly applicable, high-impact solution patterns and open-source software assets that contribute to the Microsoft platform. In this role, you will be working with data scientists, program managers and engineers from your team and our customers teams to apply your skills, perspectives, and creativity to grow as engineers and help solve our customers toughest challenges.

We are looking for a Data Scientist with expertise in developing statistical techniques to analyze data and find patterns. You will work cross-functionally with several teams including data scientists, engineering crews, product teams, and program management to deploy business solutions for Microsoft clients in the Healthcare and Life Sciences sector.

Rail Vision is a multidisciplinary startup headquartered in Ra'anana. We are the leading provider of obstacle detection & classification 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 deep learning, Rail Vision systems detect objects on and along the tracks from up to 2 kilometers away, in real-time, and in all 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 & Computer Vision engineer to join our Algorithms group What will you do?
* Be a senior researcher of the core deep learning algorithms and communicate with other researcher.
* Developing the next generation algorithms including different CNN architectures, CV algorithms and algorithms that utilize Physics in complex environment.

Advantages:

* Familiar with Electro optics devices (Thermal cameras, lenses, etc.)
* Experience working in multidisciplinary environments
* Experience in the automotive industry

As part of our continued growth, we are looking for a BizOps Analyst!
In this role, you will operate our core systems, analyze data lakes, build new monitoring methods and deliver better visibility and stability to our information services.
Responsibilities:
Develop methods with BI, RND, IT and other business units to support the information systems stability.
Monitor business applications health using a variety of technologies.
Become an application expert and support business issues and bugs around it
Build Kibana (ELK) base dashboards and SQL-based reports.
Analyze systems malfunctions in real-time using multiple analyzing and Big data tools.
Produce Root Cause Analysis post incidents and manage the process of proper fixes and future mitigation.
Manage real-time incidents, communicate with IT operators, Business users, and management, act as a focal point and lead the incident to proper resolution in the most responsible manner.