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We are seeking a hands-on Cloud DevOps Team Leader to lead the design, deployment, and optimization of secure, scalable, and cost-effective cloud infrastructure for a live cybersecurity SaaS product. You will guide a DevOps team, set technical direction, and own cloud infrastructure strategy across AWS, GCP, and Azure, with a strong emphasis on security, cost-efficiency, and production reliability.

Key Responsibilities:
Lead and mentor a team of DevOps engineers across design, automation, deployment, and operations.
Architect and maintain secure, highly available cloud infrastructure (AWS, Azure, GCP).
Design and implement complex cloud networking infrastructure - VPCs, routing, VPNs, load balancers, firewall rules - across multi-cloud and hybrid environments.
Drive Infrastructure as Code adoption (Terraform, Kubernetes, Helm) and CI/CD optimization (Argo CD).
Lead production monitoring, incident response, and troubleshooting practices to ensure system resilience.
Oversee cloud cost optimization strategies while maintaining system performance.
Ensure adherence to cybersecurity, compliance (SOC2, ISO27001), and cloud governance best practices.
Work closely with engineering, product, and security teams to align infrastructure goals with business needs.
Champion continuous improvement through team mentoring, process enhancements, and technical leadership.

Job Description:
Work within the finance department as part of the accounting team.
Manage supplier and/or customer accounts.
Perform bank reconciliations and issue invoices.
Handle payments to suppliers and various additional tasks.

Job Description:
Warehouse operations within the logistics center of a global high-tech company.
Responsibility for all stages of warehouse processes.
Work related to export operations.
Work in a physically demanding environment.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

we are looking for a AI consultant.
As an AI Consultant and a CS team member, you will work at the technological forefront of the data analytics world by helping customers adopt and realize business value through AI and Machine Learning. As a CSM you will be the customers key strategic advisor and implementer and you will work with senior stakeholders to:
Identify AI opportunities
Frame and size the value and the business impact AI can help customers realize
Drive the implementation of software and services by collaborating and managing a cross-functional account team
Ongoing account management and commercial success including value realization analysis, Quarterly Business Reviews (QBRs), Pilot process management, etc.,
Gradually develop business-ML expertise and lend this SME towards customers and our internal product development

We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

we are looking for a Senior ML Engineer.
Responsibilities:
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.