לוח משרות דרושים

It starts with you - an engineer driven to operate database systems at the highest level of reliability and performance. You care about query latency, uptime, data durability, and getting paged as little as possible. Youll operate, tune, and scale the database engines that serve the platform - from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to run the databases that power mission-critical AI at national scale, join our companys mission - this role is for you.
The Responsibilities
Operate and maintain database systems - PostgreSQL, Elasticsearch, Redis, MongoDB, vector databases, and others across cloud and on-prem.
Own database reliability - high availability configurations, replication, failover automation, and SLA adherence.
Drive performance tuning - query optimization, index design, configuration tuning, and resource profiling to meet latency and throughput targets.
Execute operational procedures - backup/recovery, disaster recovery testing, upgrades, migrations, and capacity scaling.
Lead incident response for database issues - troubleshooting production problems, root cause analysis, and implementing preventive measures.
Build monitoring and alerting - dashboards, metrics collection, slow query analysis, and proactive capacity alerts.
Enable new capabilities - deploying and tuning vector databases for AI workloads, evaluating new database technologies.
Collaborate with Data Platform, Data Engineering, Engineering, and Security teams on database operations and best practices.
Uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate safe schema evolution, partitioning, and replay/backfill practices.
Expose catalog and lineage signals - ownership, change history, and impact analysis - to improve trust and safe consumption for downstream users.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to balance performance, durability, and evolution across workloads.

At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct hands-on research and development of state-of-the-art models, algorithms, and systems.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.
Identify ambitious research directions and invent novel approaches to solve complex, high-impact problems.
Shape the research roadmap and influence long-term technical strategy across the organization.

It starts with you - a senior ML engineer responsible for building, training, evaluating, and operating machine learning systems in production. The role focuses on data pipelines, model training, experimentation, evaluation, and scalable deployment.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design, train, and evaluate ML models for production use.
Build and maintain data pipelines for training, validation, and inference.
Own experimentation workflows: feature engineering, training runs, and comparison.
Implement model evals, monitoring, and drift detection.
Package and deploy models to production systems.
Optimize training and inference performance, cost, and reliability.
Collaborate with data, platform, and product teams.
Mentor engineers and promote ML engineering best practices.

It starts with you - an engineer driven to build resilient, automated infrastructure that enables teams to move fast with confidence. You care about operational excellence, developer experience, and reliability at scale. Youll architect and operate the compute and networking infrastructure that powers our AI platform - from CI/CD pipelines to Kubernetes clusters to observability systems - across cloud and on-prem environments.
If you want to build infrastructure that powers mission-critical AI systems at national scale, join our companys mission - this role is for you.
The Responsibilities
Architect and operate Kubernetes-based infrastructure across AWS and on-prem environments, ensuring high availability, security, and performance.
Design and maintain CI/CD pipelines for application and service deployments with automated testing, security scanning, and rollback capabilities.
Drive infrastructure-as-code practices for compute and networking - building reproducible, auditable, and version-controlled infrastructure.
Own reliability and incident response - establish SLOs, build alerting systems, lead incident resolution, and drive post-incident improvements.
Enable AI-native operations - support agentic deployment pipelines, self-healing infrastructure, and secure sandboxing for model experimentation.
Build and maintain observability systems - metrics, logging, tracing, and dashboards that provide visibility into system health.
Optimize infrastructure cost and performance - right-size resources, implement auto-scaling, and identify efficiency opportunities.
Collaborate with Engineering, Data Platform, Data Engineering, and Security teams to align infrastructure with platform needs.
Shape infrastructure characteristics that support data freshness, correctness, and low-latency pathways for AI training/inference, retrieval, and agentic workflows.
Contribute paved-road tooling - reusable CI/CD patterns for services, IaC modules for compute and networking, and runbooks - that streamline delivery across teams.
Collaborate with Engineering, Data Platform, Data Engineering, Security, Product, AI/ML, Data Science, and Analytics to anticipate and meet cross-functional needs.

Were looking for a Senior Program Manager to own the execution of our Sovereign AI roadmap end-to-end. Youll sit within the Product group and act as the connective bond between Data Science, Engineering, and Product - making sure complex, cross-functional initiatives ship on time and at the quality bar our customers expect.
If you are an unblocker, enjoy making tough tradeoff calls, and drive accountability across the board, your place is with us. Youll manage multiple parallel workstreams across verticals (Security, Health, AML, and more), platform, and AI/ML domains- and youll be the person everyone relies on to know and manage where things stand and what is about to happen next.
The Responsibilities
Own and manage the full lifecycle of Sovereign AI projects from planning through delivery. Track milestones, dependencies, and risks across multiple concurrent workstreams.
Drive cross-functional alignment, and work daily with Data Science, Engineering, Product, and Design teams to ensure same direction. Break down silos and surface early mitigation.
Maintain clear, accurate visibility into project status, blockers, and timelines. Communicate proactively to stakeholders and management.
Identify and solve risks, by own and drive resolution.
Work closely with senior leadership and domain leads to ensure roadmap priorities reflect strategic goals.
Translate execution-level realities into clear decision points - when tradeoffs need to be made, you frame the options and drive alignment.
Interface with internal leadership and external government stakeholders to align on scope, timelines, and priorities. Keep information flowing in both directions.
Continuously refine processes, rituals, and tools to make the team more effective without introducing unnecessary overhead.

We are looking for an outstanding System Qualification Technician with a strong ability to understand complex systems and take an active role in the qualification of our revolutionary technologies.
Responsibilities:
Coordinate and execute hands-on functional and reliability test activities on full systems and components
Select, calibrate, and install appropriate instrumentation, including strain gauges, thermocouples, and accelerometers
Collect and analyze test data using data acquisition systems and software processing tools such as Python scripts
Evaluate test results to ensure compliance with specifications, regulations, customer expectations, and acceptance criteria in accordance with automotive standards
Generate formal technical reports and clearly present findings and conclusions to stakeholders
Conduct failure analysis investigations, diagnose failed components, and identify root causes
Perform testing activities that may require night shifts
*Employment through 3rd party.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company'sAI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The 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.

We are developing state-of-the-art LiDAR sensors and advanced perception software for the automotive industry. We are looking for a Senior System Integration Engineer to join our fast‑paced, innovative team responsible for bringing complex LiDAR systems together into a cohesive, high‑performance product. This role is ideal for a hands‑on who thrives on multidisciplinary problem‑solving, system bring‑up, and driving features from early integration through customer delivery.
Responsibilities:
Lead system integration activities across the LiDAR development lifecycle, from initial bring‑up through validation and customer deployment.
Integrate hardware, firmware, software, tools and algorithms into a unified LiDAR system, ensuring seamless functionality across disciplines.
Plan and execute system‑level integration tests, debug complex issues, and drive root‑cause analysis with cross‑functional teams.
Develop and maintain integration workflows, test setups, and automation tools to accelerate development and validation.
Collaborate on requirements refinement, system architecture discussions, and design reviews to ensure integration readiness.
Build Python‑based tools for data analysis, test automation, and rapid prototyping to support integration and characterization activities.
Support development processes aligned with Automotive SPICE and other automotive quality standards.