לוח משרות דרושים הייטק AI

Requirements:
M.Sc. in Computer Science or other relevant degrees.
Experience in data structures and algorithmic research and implementation roles in related fields
2-5 years of experience in using M/LLMs and agentic frameworks
Knowledge and experience in deep learning - NLP, computer vision, time series or standard ML
Fundamental knowledge of programming principles, substantial experience in Python and experience with MLOps practices (Git, Kubernetes, Docker, DVC - advantage)
Ability to work independently and within a team in a fast-moving environment.
Willingness to travel abroad (10%).
Curious? Us too!

Requirements:
3+ years of hands-on experience in Marketing Ops, RevOps, GTM Operations, or Growth Operations in a B2B SaaS environment.
Strong, practical HubSpot administration experience, including workflows, custom objects, lifecycle design, and complex automation.
Proven ability to design GTM architecture, not just execute isolated automations.
Very strong experience with AI-driven operations and automation, including:
Clay or similar data orchestration platforms.
AI-based enrichment, scoring, routing, or outbound workflows.
Multi-step or agent-based automation setups.
Working knowledge of Salesforce CRM and HubSpot-Salesforce integrations
Familiarity with the broader GTM tech stack such as Zapier or Make, ChiliPiper, enrichment tools, ABM platforms, and Jira.
Strong analytical mindset with the ability to translate GTM problems into scalable technical solutions.
Comfortable working independently in a highly hands-on execution role.

Requirements:
5+ years of hands-on experience in AI/ML engineering, or data science with strong engineering ownership.
Strong Python and solid software fundamentals with clean, well-tested, production-quality code.
Hands-on experience with GenAI/LLMs: prompt design, embeddings, fine-tuning and RAG patterns; experience building agents is a strong advantage.
Experience with core ML; NLP/CV/multimodal experience is a plus.
Familiarity with modern AI toolkits (e.g., LangChain, Hugging Face, PyTorch).
Cloud experience (AWS/GCP/Azure) and working with scalable data pipelines.
Strong communication and collaboration skills.
BS/MS/PhD degree in CS/Data Science/Engineering (MS/PhD a plus).

Requirements:
5+ years of experience as a Product Manager for technical products in a SaaS environment, including at least 2 years designing, launching, or actively managing products with integrated AI features, platforms, or tooling.
Strong understanding of agentic AI, autonomous workflows, and ITSM automation-a significant advantage.
Experience as an engineer or equivalent role is an advantage.
Proven track record of driving successful cross-functional teams to deliver high-impact products.
Deep technical expertise in software development methodologies, particularly for AI and automation solutions.
Outstanding analytical skills; ability to convert abstract concepts and stakeholder pain points into actionable product/AI product requirements.
Excellent communication and presentation skills for collaborating with technical and non-technical audiences.
Hands-on familiarity with Agile development methodologies and product management tools.
Bachelors degree in Computer Science, Engineering, Data Science, or a related field (preferred); advanced degrees or AI certifications are highly valued.

Requirements:
4+ years of managerial experience managing a team of business applications experts
Experience in a fast-moving tech company. Experience in a B2B SaaS company - an advantage
8+ years of hands-on experience with various business applications, including:
Salesforce - Strong proficiency is a must
Ticketing and support systems - such as Zendesk, Salesforce Service Cloud, or ServiceNow
Marketing, GTM, and enrichment systems, and integrating them into CRM - such as Hubspot, Marketing Cloud, Gong, Chilipiper, Zoominfo, and the various adtech platforms
Integrating with financial and billing Systems - such as NetSuite, Stripe, Zuora
Vast experience with integration (Workato, n8n, Zapier, Make) and API integrations
Experience with AI technologies, leading business process optimization using AI tools, and building AI processes
Analytical mindset and ability to translate business needs into scalable technical solutions.
Excellent planning, project management, communication, and presentation skills, including senior stakeholder relationships.

Requirements:
Extensive hands-on experience in Business Applications and/or software development
Experience building end-to-end AI solutions and automations
Deep understanding of business processes and a drive to impact business results
Experience with AI platforms (e.g., OpenAI, Claude, Gemini) and automation/orchestration tools (e.g., n8n, Make.com, LangChain)
Development capabilities, preferably in Python
Hands-on experience designing and consuming REST APIs, working with HTTP methods, authentication mechanisms, and integrating GTM platforms into AI-driven workflows.
High degree of independence and initiative - able to run projects autonomously
Sharp analytical skills and a structured problem-solving mindset
Excellent written and verbal communication skills; able to bridge technical and non-technical stakeholders
Passion for continuous learning, experimentation, and staying current with AI trends
Experience working with GTM or RevOps teams in a SAAS company - a big advantage
Experience with Salesforce - a big advantage.

Requirements:
Skills
Skill Requirements:
Highly familiar with AI workload and all low level processing stages. Experience in AI architectures. HW and SW view of the problem understanding the co-design tradeoffs.

Requirements:
BSc or MSc in Electrical Engineering, Computer Science, or a related field.
3+ years of experience in wireless networking, particularly in MAC-layer protocols for Wi-Fi and/or other wireless communication systems.
3+ years experience in Machine Learning/AI, working with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Solid understating of ML-pipeline: data ingestion, pre-processing, training and evaluation
Hands on experience training or fine-tuning ML Models or LLMs.
Strong programming skills in Python and/or C/C++.
Preferred / Advantage Qualifications
Familiarity with Wi-Fi standards (e.g., 802.11n/ac/ax/be) or MAC-layer concepts.
Experience with network simulators or tools (e.g., ns-3, Wireshark).
Research experience or publications in networking or AI-related domains.
PhD with a research focus in AI/ML, wireless networking, or related systems is highly desirable.

Requirements:
B.Sc. degree in computer science, computer engineering, or a closely related field
5+ years of experience in AI kernel and performance optimizations
Excellent C/C++ programming and software design skills, including debugging, performance analysis, and testing
Strong technical skills and experience with developing code in a Linux environment
Excellent teamwork and interpersonal skills
Ability to work independently, define project goals and scope, and lead your own development effort
Innovative thinking
Ways to stand out from the crowd:
M.Sc. or Ph.D. degree
Proven track record of conducting and publishing independent research
Experience in optimizing distributed deep learning pipelines with TensorFlow / PyTorch
Experience in analyzing workloads on large scale heterogeneous clusters
Hands-on experience in developing code to target heterogeneous architectures (e.g. CPU/GPU/TPU)
Experience in developing and contributing to large open-source libraries.

Requirements:
What youll need:
Excellent coding skills in Python/TypeScript, with at least 5 years of hands-on experience building reliable backend services, agents and tooling. Familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) is a strong advantage.
Experience designing, deploying, and maintaining production systems that integrate ML components, including APIs, microservices, model serving layers, feature pipelines, monitoring, and CI/CD/MLOps workflows.
Solid experience with AI related contexts Understanding of prompt engineering and LLM optimization techniques, RAG architecture
Solid understanding of distributed systems concepts, performance optimization, observability, and operating services at scale.
Strong communication skills, with the ability to bridge technical, product, and business perspectives.
Prior experience in cybersecurity, fraud prevention, or identity management is a plus, especially with secure system architectures or ML-augmented decisioning systems.
Advantages:
Experience integrating with LLM APIs (OpenAI, Anthropic Claude, etc.)
Experience with agent frameworks (LangChain, LlamaIndex, AutoGPT)
Background in ML/AI concepts and model deployment
Experience with message queues (RabbitMQ, Kafka) and event-driven architectures
Experience with function calling and tool use patterns in LLMs.

Requirements:
Technical Skills
Strong background in IT infrastructure, cloud platforms, and system architecture.
Experience with AI platforms, AI APIs, or agent-based systems.
Hands-on experience with automation and workflows tools (e.g. Workato, CI/CD, IT automation).
Familiarity with monitoring, observability, and cost management tools.
Understanding security, compliance, and governance in enterprise IT environments.
Soft Skills
Ability to translate business needs into technical AI solutions.
Strong collaboration skills across IT, security, and business teams.
Structured, architecture-level thinking with hands on execution ability.
Proactive mindset with ownership over AI enablement and automation outcomes.
Experience with AI agents, copilots, or LLM-based systems.
Knowledge of FinOps or cost management for cloud/AI services.
Experience in IT operations, ITSM, or enterprise business applications.
Familiarity with data pipelines and analytics platforms.

Requirements:
● 3+ years of experience in AI research or applied machine learning, with a focus on GPU optimization, networking, or collective communication.
● Proven experience leading and mentoring research teams.
● Familiarity with large-scale model training and inferencing, distributed AI, and collective communication libraries (e.g., NCCL, MPI).
● Experience collaborating with major industry partners and integrating research with production systems.
● Excellent communication skills, with the ability to convey complex concepts to technical and non-technical stakeholders.
● 5+ years of experience in distributed system programming
● Expert-level programming with focus on performance optimization (C / C++ / Python)
● Experience with performance profiling, benchmarking and optimization tools
● Fast learner, highly organized, detail-oriented with high motivation.

Requirements:
Minimum Qualifications
Master's in Computer Science (or related fields) or equivalent experience
Minimum 1 year hands-on experience using LLMs, ML, and other GenAI technologies to solve real problems at scale.
End-to-End Expertise with advanced GenAI techniques such as RAG (Graph/Hierarchical/etc), Agent Orchestration, Context Management, Prompt Engineering.
Solid understanding of shipping GenAI projects to production, including expertise with evaluation, optimization, and AI guardrails.
Deep proficiency with building resilient software in Python (4 years experience), including data analysis (Pandas/Polars), scripting, interfacing with APIs, concurrency.
Good understanding in one of WiFi, Bluetooth, Thread or related protocols
Excellent analytical and debugging skills
Effective communication skills, particularly with technical content
Highly organized, creative, self-motivated and passionate about achieving results.

Requirements:
5+ years backend development experience (TypeScript is an advantage)
Deep passion for GenAI, LLMs, AI Agents, and the latest developments in AI tooling
Hands-on experience with modern AI development tools like Cursor, Claude Code, and similar platforms
Familiarity with AI concepts: RAG, embeddings, mixture-of-experts, prompt crafting, LLM context engineering
Infrastructure-oriented mindset with experience scaling backend systems

Requirements:
Technical Expertise:
Programming: Advanced proficiency in Python for backend development and AI applications
GenAI Mastery: Deep understanding of large language models (LLMs) and experience with major model APIs (OpenAI, Anthropic, Google, etc.)
Multi-Agent Systems: Expertise in designing and implementing GenAI multi-agent architectures
Prompt Engineering: Advanced skills in prompt design, optimization, and engineering techniques
Cloud Platforms:
Required: Hands-on experience with AI services in at least one major cloud platform (GCP, Azure, or AWS)
Advantage: Experience across multiple cloud platforms (AI Search, Vertex AI, SageMaker, etc.)
Development Frameworks: Experience with GenAI frameworks like LangChain and cloud-based retrieval services
Software Engineering: Strong background in microservices architecture, API development, and production system design
AI/ML Fundamentals: Solid understanding of deep learning principles and GenAI techniques
Containerization (Advantage): Experience with Docker and Kubernetes for deployment and orchestration
OCR Technologies (Advantage): Experience with Optical Character Recognition systems and document processing
Data Pipelines (Advantage): Experience building and maintaining data processing pipelines
Professional Experience
Mid+ Level Experience: 2+ years in AI/ML development with significant GenAI project experience
Production Systems: Proven track record of deploying and maintaining AI solutions in production environments
Client-Facing Experience: Comfortable with technical presentations and requirement gathering sessions
Education & Background
Preferred: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related technical field
Alternative: Demonstrated industrial experience in developing deep learning and GenAI solutions (degree not required with strong portfolio)
Soft Skills
Problem-Solving: Excellent analytical and creative problem-solving abilities
Communication: Strong technical communication skills for both technical and non-technical audiences
Collaboration: Proven ability to work effectively in cross-functional teams
Adaptability: Thrives in fast-paced environments and eager to learn emerging technologies
Consulting Mindset: Ability to understand client needs and provide strategic technical guidance.