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Requirements:
At least 2 years of experience in working with networking, different operating systems (Windows, Linux)
In-depth knowledge of networking and protocols, including a strong grasp of TCP/IP fundamentals and widely used protocols such as DNS, HTTP(S), SMTP, FTP, and VOIP (SIP, H.323)
The advantage for applicants with knowledge in Site-to-Site VPN
The advantage for applicants with knowledge in Dynamic Routing protocols such as BGP, OSPF, etc.
Very good English skills (spoken, written).
Availability for a full-time position, overtime may be required on occasions.
Experience and knowledge with performance test tools - Advantage
Working experience with cloud-based platforms as AWS, Azure, etc. - Advantage
Familiarity with network security testing methodologies
Familiar with Jira
Familiar with scripting or programming - Advantage.

Requirements:
B.Sc. in Computer Science or a related field (must)
1+ year of software development experience
Comfortable working in a Linux environment
Deep understanding of networking concepts, including the TCP/IP stack, OSI model, and routing
Proficiency in Python and Bash scripting
Good familiarity with C
Strong coding, design, debugging, and troubleshooting skills
Hands-on experience using AI-assisted development tools as part of daily engineering work
Strong communication skills and ability to work effectively as part of a team
Advantages
Knowledge of Linux OS internals, such as the kernel networking stack, device drivers, and core subsystems
Experience working on security gateways, such as firewalls, VPN gateways, or deep packet inspection components
Background in cyber security or network security
Strong analytical and problem-solving skills
Fast learner with the ability to quickly understand complex systems
Ability to work in a dynamic, multi-tasking environment.

Requirements:
Bachelors degree in Economics, Business Administration, Industrial Engineering, or a related field
3+ years of relevant experience in a global sales organization, ideally within GTM or RevOps
Deep understanding of GTM operating models and the role of Revenue Operations in driving predictable growth
Hands on experience with forecasting processes, executive reporting, and senior leadership cadences
Proven, practical experience working directly with Salesforce and Clari as core operational systems
Strong analytical and business oriented thinking, with the ability to synthesize complex information into clear insights
Excellent interpersonal communication and stakeholder management skills; able to influence without authority
High EQ, maturity, and comfort operating in fast paced, high visibility environments
Strong command of Excel, Power BI, and familiarity with modern data platforms such as Snowflake.

Requirements:
Experience:
Technical Expertise:
3+ years of experience in technical support (Tier 3), professional services, or a customer-facing role within the cybersecurity or cloud computing fields.
Strong familiarity with cloud and SaaS environments (AWS, Azure, GCP)
Experience troubleshooting and debugging application-related issues in distributed cloud-based systems.
Experience with Kibana, Elasticsearch or similar
Strong knowledge of networking concepts and protocols, including TCP/IP, DNS, HTTP/S, VPNs, routing, and traffic analysis.
Hands-on experience with firewalls, network security platforms (from vendors such as our company, Palo Alto Networks, Fortinet, Cisco, or similar.), firewall policies, access control, and enterprise security architectures.
Automation and Scripting:
Proficiency in scripting or automation tools and languages such as Python, Bash, or similar.
Communication and Problem-Solving:
Exceptional analytical and troubleshooting skills, particularly with application-level issues.
Strong verbal and written communication skills to bridge technical concepts for diverse audiences.
Key Attributes:
Keen attention to detail with a proactive mindset.
Ability to independently manage multiple high-priority issues simultaneously.
Collaborative team player with the ability to work effectively across departments.
Customer-centric approach with a strong passion for resolving technical challenges.
Advantages:
Familiarity with containerization technologies (e.g., Docker, Kubernetes).
Experience analyzing network traffic using tools such as Wireshark, tcpdump, or similar.
Hands-on experience with cybersecurity technologies and tools such as SIEMs, NIST frameworks, Nuclei, Shodan, etc.
Knowledge of application security practices and protocols.
Prior Experience in Intelligence
Experience with Data Pipelines
Experience working with Salesforce as a ticketing system
Familiarity with Jira.

Requirements:
What You Bring
Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related engineering discipline, or equivalent practical experience.
5+ years of professional software engineering experience, including substantial experience building backend systems, distributed systems, or data-intensive applications in production environments.
Strong Python engineering skills, including modular architecture, dependency management, testing practices, observability, and production-grade code quality.
Strong SQL and data modeling expertise, including schema design, indexing strategies, event-driven data models, and scalable analytical aggregations.
Hands-on experience building incremental and idempotent data pipelines that handle duplicate, invalid, and late-arriving events without impacting downstream consumers.
Experience with at least one major cloud platform (Azure, GCP, or AWS) and modern lakehouse technologies such as Databricks, Delta Lake, Spark, or equivalent architectures.
Experience with streaming or messaging technologies such as Kafka, Pub/Sub, Event Hubs, or similar event-driven systems.
Proven ability to diagnose and resolve production data issues, including data quality problems, schema evolution, backfills, replay scenarios, and performance bottlenecks.
Strong written and verbal communication skills in English and experience collaborating effectively with globally distributed teams.

Nice to Have
Experience building industrial, IoT, manufacturing, or operational data platforms.
Familiarity with Digital Twin architectures and industrial data models.
Experience with graph databases, context graphs, knowledge graphs, or relationship-centric data modeling.
Exposure to AI/LLM-powered applications, including retrieval-augmented generation (RAG), agents, tool calling, or evaluation frameworks.
Experience working with Databricks or similar lakehouse platforms from both application and platform perspectives.
Experience building data products that directly support AI agents, intelligent applications, or machine learning workflows.

Requirements:
B.Sc. in Electronics Engineering is a must
Deep understanding of electronic design and DFM - must
Understanding multidisciplinary products design
At least 5 years of experience with worldwide compliance / regulations - must
Knowledge in electronics components, PCB and PCBA design and assembly process, batteries, radio frequency (RF), IR, testing methods, and knowledge in ATE (Automatic Test Equipment)
At least 5 years of experience in board design with Altium or OrCAD - Advantage
Communication skills verbal, written, and presentation skills in both Hebrew & English is must.
Experience in matrixed worldwide organization and ability to work well in a team environment including cross-culture.
Self-motivated and organized.
Ability and willingness for hands-on assignments
Required Skills:
Accountability, Communication, Electrical Engineering

Requirements:
What You Bring
5+ years of professional software engineering, MLOps, or ML platform engineering experience in production environments.
Significant experience building or owning production ML infrastructure and lifecycle systems.
Strong Python engineering skills with production-grade architecture, modular design, testing, packaging, and robust error handling.
Strong understanding of the end-to-end ML lifecycle including training, deployment, monitoring, retraining, reproducibility, and lineage.
Experience working with large-scale data platforms such as Databricks, Spark, Delta Lake, or equivalent ecosystems.
Experience with ML platform and MLOps frameworks such as MLflow, Metaflow, Kubeflow, or equivalent ML lifecycle-management systems.
Proven ability to design reusable workflow orchestration using Airflow, Metaflow, or Databricks, covering automation, scheduling, dependency management, and production reliability.
Familiarity with operational patterns for LLMOps, AgentOps, and production AI systems.
Strong written and verbal communication skills in English.

Nice to Have
Experience with industrial, IoT or manufacturing platforms.
Experience with feature stores, model registries, dataset versioning, and lineage systems.
Experience with AI agents, RAG systems, production GenAI applications, or evaluation frameworks.

Requirements:
You Will Bring
6+ years of professional software engineering experience.
Strong Python development skills.
Strong backend engineering background, including APIs, services, integrations, or microservices.
Proven experience designing, shipping, or operating LLM-powered applications or GenAI systems.
Experience with RAG, AI agents, tool/function calling, prompt orchestration, evaluation, and observability.
Experience with microservices, distributed systems, and production backend architecture.
Strong understanding of system design, reliability, security, scalability, latency, and maintainability.
Ability to work with complex data models and expose them safely through AI systems.
Ability to operate in ambiguous technical areas and turn prototypes into production-ready systems.
Strong communication skills and ability to explain technical decisions clearly.

Preferred Qualifications
Experience with LangChain, LangGraph, or LangSmith.
Experience with Go, MongoDB, Databricks, Kubernetes, Docker, REST APIs, vector search, or event-driven systems.
Experience with Azure OpenAI, Gemini, or similar LLM platforms.
Experience building or using knowledge graphs, GraphRAG, or graph databases such as Neo4j.
Experience building multi-agent systems or orchestrating multiple specialized agents/tools in production.
Experience building internal platforms, SDKs, developer tools, or shared engineering infrastructure.
Experience with authorization, data segregation, multi-tenant systems, or user-level data scoping.
Experience in industrial, IoT, predictive maintenance, manufacturing, or operational-data domains.

Requirements:
Advanced degree (M.Sc. or Ph.D.) in Physics, Electrical Engineering, Computer Science, Mathematics, or a related quantitative field.
Over 4+ years of experience, demonstrated expertise in DSP-based methods (e.g., STFT, FFT, Hilbert, Wavelet, etc.), to extract features and anomalies from the data.
Over 2 years of professional experience in ML/AI, with a proven track record in modeling and analyzing complex time-series data.
Proven technical leadership experience in large-scale, multidisciplinary projects.
Hands-on experience working with real-world physical data and sensor signals.
High proficiency in Python for the full development lifecycle, including model deployment and performance monitoring.
Ability to independently research, architect, and implement innovative technological solutions.
Prior experience in the industrial or manufacturing sector is advantageous.
Capability to translate theoretical research into robust, scalable, and production-ready systems.
Experience thriving in agile environments with a focus on rapid iteration, continuous feedback, and professional growth.
Excellent communication skills for collaborating with cross-functional teams, including Product Management and Engineering.

Requirements:
3+ years of experience as a data, product, or business analyst, ideally at a fast-growing consumer company
A degree in Industrial Engineering, Mathematics, Statistics, or a related field
Strong SQL skills and hands-on experience with BI tools (Looker, Tableau, Mixpanel, or similar)
Familiarity with A/B testing best practices and comfort working with complex datasets
The ability to work fluidly across product managers, data engineers, and data scientists, and to communicate technical findings clearly in English
Ready to work in an office environment most days of the week

Requirements:
Advanced degree (M.Sc. or Ph.D.) in Physics, Electrical Engineering, Computer Science, Mathematics, or a related quantitative field.
Over 4+ years of experience, demonstrated expertise in DSP-based methods (e.g., STFT, FFT, Hilbert, Wavelet, etc.), to extract features and anomalies from the data.
Over 2 years of professional experience in ML/AI, with a proven track record in modeling and analyzing complex time-series data.
Proven technical leadership experience in large-scale, multidisciplinary projects.
Hands-on experience working with real-world physical data and sensor signals.
High proficiency in Python for the full development lifecycle, including model deployment and performance monitoring.
Ability to independently research, architect, and implement innovative technological solutions.
Prior experience in the industrial or manufacturing sector is advantageous.
Capability to translate theoretical research into robust, scalable, and production-ready systems.
Experience thriving in agile environments with a focus on rapid iteration, continuous feedback, and professional growth.
Excellent communication skills for collaborating with cross-functional teams, including Product Management and Engineering.

Requirements:
What You Bring
Agentic-First Mindset & Proven Experience as an AI-Native Engineer utilizing tools like Claude, Cursor, or Gemini to enhance productivity and quality in commercial development.
5+ years of mobile development experience with proficiency in Flutter/Dart and native iOS/Android, BLoC state management, and designing scalable mobile architecture.
Comfortable with full-stack contributions to backend and frontend services/APIs to ensure end-to-end feature ownership. Proven ability to write high-quality, testable Dart code with cross-platform (iOS/Android) and RTL familiarity.

Strong Advantage
Experience with industrial IoT and field-service applications, including device commissioning workflows, hands-on IoT connectivity (Wi-Fi, NFC, BLE, and Beacons APIs), and familiarity with AR and Indoor Navigation.
Familiarity with Firebase, third-party support tooling (Intercom), and Offline/Sync capabilities.

Requirements:
M.Sc., or Ph.D. in Electrical Engineering, Computer Science, Physics, Mathematics, or a related field.
4+ years of experience in ML applications, including research on time-series data, ML-based vectoring, and Embeddings (as Transformers, TGNN, TSFM, Graph Transformer, GNN, CNN, etc.)
Proficiency in Python (Pytorch, Pandas, NumPy, PyG - nice to have), and Applied Science SDLC - Discovery, Research, development, fidelity, deployment, monitoring, Training, and fine-tuning
Experience in anomaly detection, abnormal behavior, outliers, pushing recall, precision, and tail metrics KPIs boundaries
Experience working with ML infrastructure such as MLFlow, Vertex AI, Sagemaker etc.
The ability to translate research into scalable, production-ready solutions.
Experience working on Agile teams with a passion for fast iterations, feedback, and continuous learning.
Proven ability to collaborate with diverse, cross-functional groups, including product managers, infrastructure, and data engineering teams.
Experience in feature engineering-based signal processing - a big advantage.

Requirements:
Experience scaling high-performing engineering organizations through fast-growth phases, with a track record of raising the bar on delivery and quality
A leadership style that sets high standards, leads by example, and creates accountability without losing the team
Comfort operating in a product-led environment, where engineering and product move together
Strong communication skills, with the ability to give direct feedback, recognize great work, and build trust across levels
A genuine belief in meritocracy, where hiring and growth decisions are driven by skill, performance, and motivation
A bachelor's degree in Computer Science, Software Engineering, or a related technical field
Ready to work in an office environment most days of the week

Requirements:
M.Sc., or Ph.D. in Electrical Engineering, Computer Science, Physics, Mathematics, or a related field.
5+ years of experience in ML applications in modeling Time-series data, & ML-based vectoring, and Embeddings for insight & recommendations systems (Transformers included) - Mandatory.
2+ years of experience in LLM and Agentic applications, Eval tools, methods, and workflows (HITL, LLM-as-a-judge, deterministic, Metrics & Embeddings), Fine-Tuning, and AI workflows and lifecycle (e.g. LangSmith, CrewAI, LangGraph, Embedding (BERT, w2v, FastText, FastEmbed, GloVe, etc.), Tokenizations (GPT. TikToken, Token validators, etc.), & Vector Similarities & search methods.
Proficiency in Python for model development, deployment, and monitoring.
Experience working on Agile teams with a passion for fast iterations, feedback, and continuous learning.
Proven ability to collaborate with diverse, cross-functional groups, including product managers, infrastructure, and data engineering teams.
The ability to translate research into scalable, production-ready solutions.
Experience in anomaly detection and AI/ML - an advantage.
Experience in feature engineering-based signal processing - an advantage.
Experience in optimizing costs of API calls - Nice to have.