לוח משרות דרושים עבודה היברידית

We are looking for a Senior Back-end Engineer who will develop solutions that transform unstructured electronic communication data (from phone calls, chats, emails, etc.) into actionable intelligence for financial institutions.

What Youll Do:
Design and implement feature requests.
Optimize system scalability and resilience.
Work closely with the Product Team and Architects.
Support and maintain the production environments.

We are looking for a highly skilled and motivated Machine Learning Engineer to join our Data Science Engineering team. The ideal candidate will have a deep understanding of machine learning infrastructure and solutions, enabling data scientists and engineers to efficiently develop, deploy, and maintain models in production by delivering a scalable and high-quality solution. This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams.

What Youll Do:
Develop and maintain machine learning infrastructure and solutions to support the efficient development, deployment, and maintenance of models in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models.
Design and implement software architecture for machine learning solutions.
Optimize model deployment and serving using industry best practices with CPU, GPU, and external APIs.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Collaborate with the DevOps team to establish best practices for MLOps.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning and related technologies.

This role is responsible for leading the FinOps practice across our Financial Compliance, ensuring optimal use of cloud resources, managing cost predictability, and maintaining financial discipline across all business units. The specialist will own and evolve the internal product pricing calculator and provide continuous insight into the expected and actual cost structure of our AWS-hosted, Kubernetes-based multi-tenant architecture.

This is a hybrid technical-financial role requiring advanced understanding of cloud architecture and pricing models, alongside financial acumen for forecasting, budgeting, modeling, and performance reporting.

What youll do:

1. Product Pricing Ownership:
Maintain and evolve the internal AWS product pricing calculator.
Translate complex Kubernetes deployment models and service configurations (e.g., OpenSearch, EKS, data transfer patterns) into actionable cost models.
Incorporate cost variability into pricing decisions, including compute, storage, cross-region transfers, and scaling dynamics.
Work with the CTO to align technical design with pricing logic and cost structure.
2. Cloud Cost Management and Optimization:
Monitor real-time cloud consumption data across our environments (POC, production, demo, development).
Identify inefficiencies and over-provisioning, recommend rightsizing and reserved instance/savings plans strategies.
Set and enforce budgets per business unit, project, or environment.
Design and implement alerts, dashboards, and reporting in tools such as Anodot, AWS Cost Explorer, CloudWatch, or custom BI tools.
3. FinOps Culture Champion:
Act as the central cost optimization authority across CloudOps, DevOps, Delivery, and R&D teams.
Run bi-weekly/quarterly cost review cadences and publish cost health dashboards.
Educate teams on cost-efficient architecture, usage of spot instances, caching, storage lifecycle rules, etc.
Promote accountability by assigning cost KPIs and budget adherence metrics.
4. Management Reporting and KPI Tracking:
Generate executive-level insights and forecasts on cloud cost trends, anomalies, and risks.
Define and report against key FinOps KPIs such as cost/unit, cost of service, cost per deployment, budget variance, forecast accuracy.
Provide decision-making support to management based on real-time and retroactive data analysis.

We are looking for a skilled and motivated Engineering Tech Lead to join our Data Science Engineering team. The ideal candidate will have a deep understanding of software development and the ability to guide technical solutions. This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams. As an Engineering Tech Lead, you will play a crucial role in exploring and investigating solutions and technologies, contributing to technological and architectural decisions with a hands-on approach.

What Youll Do:

Develop and maintain software infrastructure and solutions to support the efficient development, deployment, and maintenance of machine learning models and our surveillance pipe solution in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models and a fully integrated scalable solution.
Design and implement software architecture for machine learning solutions.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning, software development, and related technologies.

Required Instructional Designer & LMS Admin
You will join our Information Systems domain as part of the LMS team. The team is responsible for providing ongoing system administration and support, gathering business requirements and designing learning solutions and implementing onboarding workspace and training libraries for units and more.
In this role, you will identify knowledge gaps, develop, implement, and manage training programs for various internal business customers, including the Information Systems domain and R&D units. You will also collaborate with the Learning and Development HR unit to create learning materials and deliver support to key stakeholder.
What will your job look like:
Developing and delivering learning materials and training programs, including technological/technical training materials.
Supporting and advising users and workspace managers on best practices within our Learning Management System (LMS).
Executing implementations and designs in the learning system.
Managing and operating the ticketing system to provide service to internal customers
Our hybrid policy: 4 days in the office. 3 days in Jerusalem, 1 day at another site (Petah Tikva/ Tel Aviv /Ramat Gan), and 1 day remote.

A world leader in driver assistant systems and autonomous vehicles, is looking for talented silicon validation engineer for the range of its next generation SoCs supporting its radar systems.
Our team is responsible for validating our radar SoCs, utilizing Pre-Silicon environments, as well as Post-Silicon platforms.
We are developing fully embedded C++ based validation environment for our needs.
You will be taking part in developing anything from environment and drivers through system modules such as file system, network stack, memory management and more, and up to complex automation tools in both C++ and python.
What will your job look like:
Get a deep understanding of our chip hardware IP blocks, both analog and digital.
Develop our validation environment.
Develop, port, or add features to the product drivers using Technical Specs and existing modules.
Define, develop and execute various complex validation scenarios on the SoC.
Debug complex SoC problems using embedded GDB, JTAG probes, going down to signal level using scopes.
Take part in Next Gen SoC's Power-On's and platforms Bring-Up's.
Collaborate with other SW/Embedded and HW/Electrical Validation teams across the company.