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Required Senior NLP Researcher
Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

Rwquired Senior DevOps Engineer - AI Infra Group
Responsibilities
Build and maintain CI/CD pipelines and Kubernetes clusters (cloud + on-prem).
Implement Infrastructure as Code (Terraform, Ansible, Helm) and GitOps practices.
Automate deployment, monitoring, and scaling workflows.
Collaborate with engineers to improve developer experience and system reliability.
Ensure observability, security, and compliance across infrastructure.

Required Senior Data Scientist
Tel Aviv Full-time.
Responsibilities
Conduct hands-on research and development of cutting-edge models
Take research projects from ideation to deployment and production
Work closely with domain experts and the engineering department to improve and create new innovative solutions.
Help define the AI product roadmap.

Were looking for an experienced AI Project Manager to lead and coordinate cross-functional projects within our AI Group. You will partner with research, data science, and product leaders to translate strategy into action, managing timelines, dependencies, and priorities for our most advanced AI initiatives.
Responsibilities
Lead the planning, execution, and delivery of multiple AI projects across research and production teams.
Partner with AI scientists, ML engineers, and product stakeholders to define goals, success metrics, and execution plans.
Establish and maintain clear project roadmaps, ensuring alignment with the AI Groups strategic priorities.
Manage communication across technical and non-technical stakeholders, providing visibility into progress and blockers.
Drive agile processes within AI teams to support experimentation, iteration, and scalable delivery.
Identify and mitigate project risks, ensuring smooth collaboration across research, data, and engineering functions.
Promote a culture of technical rigor, transparency, and innovation within the AI Group.

Required MLOps Engineer - AI Infra Group
Tel Aviv Full-time
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world production-grade AI infrastructure. This group builds scalable, high-performance AI systems for internal users and external customers, designed to run seamlessly across cloud and on-premise environments using the latest hardware advancements.
Responsibilities
Design, build, and maintain scalable Kubernetes-based infrastructure for ML workloads across on-premise and cloud environments
Architect hybrid infrastructure solutions enabling seamless model flow from on-premise training environments to cloud-based inference deployments
Implement model registry and artifact management strategies that support cross-environment synchronization, versioning, and governance
Design secure, efficient data and model transfer mechanisms between on-premise and cloud (networking, storage replication, caching strategies)
Implement and manage GPU scheduling, resource allocation, and cluster autoscaling for heterogeneous compute environments
Build and maintain CI/CD pipelines for ML systems, including model versioning, testing, and promotion across environments
Develop observability solutions (logging, monitoring, alerting) for ML infrastructure across hybrid deployments
Collaborate with ML Engineers to define infrastructure requirements and SLAs for training and serving workloads.

Required ML Engineer - AI Infra Group
Tel Aviv Full-time
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world production-grade AI infrastructure. This group builds scalable, high-performance AI systems for internal users and external customers, designed to run seamlessly across cloud and on-premise environments using the latest hardware advancements.
Responsibilities
Design and optimize LLM serving infrastructure using inference engines (vLLM, TensorRT-LLM, Triton Inference Server)
Implement and tune distributed inference strategies including tensor parallelism, pipeline parallelism, and multi-node serving
Develop and apply model compression techniques to optimize cost, latency, and memory footprint while maintaining model quality
Build self-service fine-tuning platforms that enable data scientists to run experiments (LoRA, QLoRA, full fine-tuning) in a standardized, reproducible, and governed manner
Optimize inference performance through batching strategies, KV-cache tuning, and speculative decoding
Develop reusable APIs, abstractions, and platform services for model deployment, scaling, and lifecycle management
Collaborate with AI researchers and product teams to productionize models and meet latency/throughput requirements
Evaluate and benchmark new model architectures, compression methods, and serving frameworks.

Required Data Engineer - AI Infra Group
Tel Aviv Full-time
The Job
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world data platforms. You'll architect and ship our streaming lake-house and data platform, turning billions of raw threat signals into high-impact, self-serve insights that protect countries in real time all while building on top-of-the-line technologies, such as Iceberg, Flink, Paimon, Fluss, LanceDB, ClickHouse and more.
Responsibilities
Design and maintain agentic data pipelines that adapt dynamically to new sources, schemas, and AI-driven tasks
Build self-serve data systems that allow teams to explore, transform, and analyze data with minimal engineering effort
Develop modular, event-based pipelines across AWS environments, combining cloud flexibility with custom open frameworks
Automate ingestion, enrichment, and fusion of cybersecurity data including logs, configs, and CTI streams
Collaborate closely with AI engineers and researchers to operationalize LLM and agent pipelines within the CLM ecosystem
Implement observability, lineage, and data validation to ensure reliability and traceability
Scale systems to handle complex, high-volume data while maintaining adaptability and performance
Own the data layer end-to-end including architecture, documentation, and governance.