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The Senior Machine Learning Engineer GenAI is responsible for designing, implementing, and operating large-scale systems and tools for AI model benchmarking, optimization, and validation. Unlike a traditional ML Engineer focused primarily on model training, this role centers on building the infrastructure, automation, and services that enable systematic evaluation and performance tuning of LLMs at scale.

This position combines deep understanding of model serving frameworks, GPU optimization, and benchmarking methodologies with strong software engineering skills to deliver reliable, reproducible, and production-grade evaluation pipelines. The engineer will design and maintain validation-as-a-service platforms that allow internal and external stakeholders to assess models across latency, throughput, accuracy, and cost dimensionsintegrating seamlessly with our AI ecosystem and industry-standard GenAI tooling.

A core aspect of this role is creating a robust, extensible benchmarking and validation framework capable of running across diverse inference engines, hardware configurations, and deployment environments, while providing actionable insights for model selection, optimization, and integration.

What you will do:
Benchmarking Platform Development: Design and implement scalable benchmarking pipelines for LLM performance measurement (latency, throughput, accuracy, cost) across multiple serving backends and hardware types.

Optimization Tooling: Build utilities and automation to profile, debug, and optimize inference performance (GPU utilization, memory footprint, CUDA kernels, parallelism strategies).

Validation-as-a-Service: Develop APIs and self-service platforms for model evaluation, enabling teams to run standardized benchmarks on demand.

Serving Integration: Integrate and operate high-performance serving frameworks (vLLM, TGI, LMDeploy, Triton) with cloud-native deployment patterns.

Dataset & Scenario Management: Create reproducible workflows for dataset preparation, augmentation, and scenario-based testing to ensure robust evaluation coverage.

Observability & Diagnostics: Implement real-time monitoring, logging, and metrics dashboards (Prometheus, Grafana) for benchmark and inference performance.

Cloud-Native Orchestration: Deploy and manage benchmarking workloads on Kubernetes (Helm, Argo CD, Argo Workflows) across AWS/GCP GPU clusters.

Integration with GenAI Tooling: Leverage Hugging Face Hub, OpenAI SDK, LangChain, LlamaIndex, and internal frameworks for streamlined evaluation workflows.

Performance Engineering: Identify bottlenecks, apply targeted optimizations, and document best practices for inference scalability.

Ecosystem Leadership: Track emerging frameworks, benchmarks, and optimization techniques to continuously improve the evaluation platform.

The Consulting team is looking for an Architect focused on our Cloud Products to join us in Raanana. In this role, you will specialize in the design and development of cloud-ready Infrastructure and application architectures, including automated container platforms, deployment pipelines. You'll lead the on-site implementation of our technologies like our OpenShift, our OpenShift Data Foundation, our Smart Management and our Ansible Automation Platform. You'll play a key role in the enterprise development of our customers, helping make our solutions both practical and workable for their businesses. You'll work to gain an understanding of customer infrastructure and business needs, make recommendations that resolve their issues, and help them make strategic decisions.

As a Cloud Architect, you will help customers build enterprise applications and capabilities around cloud technologies to streamline development and allow for continuous feature release of Infrastructure and applications.

If you have hands-on devops architecture & design experience and are prepared to work from customer site we'd love to hear from you!


What you will do:

Serve as a subject matter expert at the customer site, with a strong hands-on focus addressing technical, development, and strategic IT requirements through hands-on implementation and direct engagement.

Understand industry practices and our policies, procedures, and values.

Demonstrate good judgment in selecting best methods to obtain solutions.

Implement and integrate our open and hybrid cloud solutions including our OpenShift and other our offerings.

Team up with our customers to rapidly build application prototypes using modern application development practices and open source emerging technologies.

Manage and gain understanding of domains like micro services, API management, and web- scale architectures, DevOps engineering and application delivery, container-based continuous delivery (CD), cloud automation, and everything-as-code.

Collaborate with project and customer team members to meet timelines and goals.

Contribute to project documentation and diagrams, including ticket or bug management.

Mentor and share your knowledge with customers and the existing team.

Define and promote the adoption of automation techniques and DevOps processes to improve the cloud life cycle, including infrastructure and application uptime, availability, and time-to-market.

Implement solutions using cloud technologies, design principles, integration points, and automation methods.

Handle tough problems in an innovative way .

Join the Workload Availability team as a Software Engineer in Ecosystem Engineering. Your core mission is to safeguard the stability and availability of mission-critical workloads on our OpenShift by developing and integrating robust proactive and reactive remediation mechanisms. You will focus on the complex challenges of node health checking, automated fencing, and self-healing within the cluster, ensuring these critical availability features integrate seamlessly with the diverse ecosystem of third-party hardware, cloud platforms, and infrastructure providers.

What You Will Do

Maintain critical components, controllers, and operators (primarily in Go) responsible for detecting, diagnosing, and automating the recovery of unhealthy cluster nodes on OpenShift.

Become responsible for the quality of our offerings, participate in peer code reviews and continuous integration (CI), and software release process using Konflux CI/CD system.

Develop intelligent node mechanisms to accurately determine a node's operational status and trigger the appropriate self-healing or external remediation actions.

Contribute upstream to projects that focus on Kubernetes-native machine and node remediation to advance the platform's self-healing capabilities.

Troubleshoot and resolve complex cross-ecosystem availability and reliability failures, requiring deep debugging into kernel-level behavior, cloud infrastructure APIs, and Kubernetes control plane logic.

Proactively utilize AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.

The Opportunity: We are seeking a highly experienced and visionary Director, Data &
Analytics to lead our data organization. Reporting directly to the VP of Data, GRC, IT, and
Security, you will be responsible for defining and executing Teads' data strategy, ensuring the
reliability, scalability, and impact of our data assets. You will lead five critical domains: BI
Engineering, Data Engineering, Data Platform, BI Product, and BI Labs (Data Science),
fostering a culture of data excellence, innovation, and partnership across the company.
This role requires a unique blend of deep technical expertise, strong leadership capabilities, and
a keen understanding of how data can drive business value in a fast-paced, data-intensive
environment.
What will you do?
Strategic Leadership: Develop and execute a comprehensive data strategy aligned with Teads' business objectives. Identify emerging data trends and technologies, and drive their adoption to maintain a competitive edge.
Team Leadership & Development: Lead, mentor, and inspire five diverse teams (BI Engineering, Data Engineering, Data Platform, BI Product, BI Labs), comprising talented engineers, analysts, product managers, and data scientists. Foster a high-performance culture, promoting continuous learning, collaboration, and career growth.
Data Engineering & Platform Ownership: Oversee the architecture, development, and maintenance of Teads' core data infrastructure, including data lakes, data warehouses, ETL/ELT processes, and real-time data pipelines. Ensure data quality, availability, and governance across all data assets.
Business Intelligence & Analytics Enablement: Drive the development of robust BI solutions, semantic models, and reporting infrastructure that empower business users with actionable insights.
Data Science & Advanced Analytics: Guide the BI Labs team (Data Scientists) in applying advanced analytical techniques, machine learning, and statistical modeling to solve complex business problems, identify business opportunities, and promote AI for predictive analytics .
Cross-Functional Collaboration: Partner closely with engineering, product, R&D, sales, marketing, and finance teams to understand their data requirements, deliver impactful data solutions, and evangelize data-driven decision-making across the organization.

We are seeking an experienced Business Applications Team Leader with at least five years of expertise in Salesforce administration and SaaS applications. This role focuses on leading a team, managing strategic projects, and optimizing core business systems, with Salesforce serving as the foundation. You will ensure seamless collaboration between stakeholders, drive innovation through AI-powered solutions, and uphold SOX compliance requirements across business systems. This is an exciting opportunity to contribute to a high-growth AdTech/SaaS company by delivering impactful and scalable solutions.
What will you do?
Lead, mentor, and manage a team of Salesforce Administrators and SaaS specialists.
Oversee the configuration, optimization, and integration of the Salesforce platform to align with business objectives.
Implement AI-driven tools and solutions to enhance automation, reporting, and decision-making.
Ensure SOX compliance for all applicable systems by maintaining robust controls, audit readiness, and data governance frameworks.
Collaborate with cross-functional teams to identify technology needs and deliver well-aligned solutions.
Continuously improve system performance and usability by staying informed of new technologies and best practices.

We are looking for a Data Scientist with deep experience in the advertising industry to join a team of passionate engineers who build advertising solutions at world scale. We build and operate large-scale distributed machine learning systems that process 1B predictions per second during real-time auctions.
What will you do?
As a Senior Data Scientist, your mission will be to:
Stay on top of the state-of-the-art science and technology of large scale advertising systems
Areas of interest are models for CTR and CVR, on-line learning regimes, cold start, efficient and effective embeddings for users, ads and similar, ad matching, two tower architecture, ad match, ad ranking, etc.
Work with teams of data scientists and machine learning engineers to identify investment opportunities
Help the teams implementing the solutions - on multiple projects as an advisor and on projects you select as a part of the implementation team where you will be expected to participate in bringing new projects to production environment
Work with product managers to find data science and AI projects with best cost/benefit risk/reward ratios
Spend time experimenting with new approaches by yourself
Follow industrial and academic research, occasionally publish at conferences.