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חברה חסויה
Location: Ra'anana
Job Type: Full Time
Required ML-Engineering Lead
What You Will Do:
End-to-End Ownership: Lead the full technical execution of ML projects, ensuring every stage-from data acquisition to deployment-meets our rigorous standards.
R&D Collaboration: Partner closely with R&D departments to design data collection strategies and integrate ML-based tools and agents into their specialized workflows.
Versatile Implementation: Develop models and intelligent systems for a variety of use cases, ranging from real-time field performance to autonomous research-support tools.
Technical Authority: Act as a founding voice for ML implementation and strategy within the CTOs office.
Requirements:
M.Sc. in Electrical Engineering, Computer Science, or a related technical field.
At least 7 years of experience building, training, and deploying ML models.
Proficiency in Python and deep familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow).
Experience building AI agents (e.g., RAG systems, agentic workflows, or tool-calling implementations) is a significant plus.
Proven ability to take a machine learning task from the research phase to a fully implemented and evaluated solution.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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12/08/2026
חברה חסויה
Location: Ra'anana
Job Type: Full Time
Required Senior Agentic Systems Engineer
Israel - Raanana
We dont limit our challenges. We challenge our limits. Always. Were ambitious. Were game changers. And we play to win. We set the highest standards and execute beyond them. And if youre like us, we can offer you the ultimate career opportunity that will light a fire within you.
So what is the role all about?
The Senior Agentic Systems Engineer is a hands-on engineer who designs, builds, and operates AI-powered tools and workflows for engineering teams.
Were looking for builders who are not only users of AI tools, but can design autonomous agentic systems, optimize model usage, create reusable agents and workflows, and orchestrate complex multi-step work across multiple tools and agents.
Youll be a one-person-army builder: able to understand a problem, define the approach, build the backend, create a simple UI when needed, integrate APIs, connect agents, automate workflows, and deliver working tools quickly.
How will you make an impact?
Build centralized AI-powered tools for engineering teams.
Create and maintain agents, skills, hooks, MCP servers, plugins, and workflow automation.
Design autonomous agentic systems for internal engineering use cases.
Build multi-step AI workflows across code, documentation, Jira, GitHub, CI/CD, and internal systems.
Build tools for PR review support, test generation, documentation updates, spec creation, codebase understanding, and developer productivity.
Learn from local teams and convert successful solutions into reusable centralized assets.
Integrate AI tools with GitHub, Jira, Confluence, CI/CD, internal portals, and engineering systems.
Optimize AI workflows for cost, latency, quality, and reliability.
Apply token economy thinking when designing agents, prompts, MCP usage, RAG flows, and tool integrations.
Contribute to the internal AI marketplace and reusable asset catalog.
Work directly with engineering teams, collect feedback, and iterate quickly.
Requirements:
Strong practical experience with LLMs and AI-assisted development.
Experience designing, building, and orchestrating autonomous agentic systems and multi-agent workflows for internal or external automation.
Experience with agents, skills, MCP servers and development, plugins, RAG, embeddings, and AI orchestration frameworks.
Ability to orchestrate complex, multi-step work across cooperating agents and tools.
Deep understanding of token economy, model selection, prompt/context design, and AI workflow optimization for cost, latency, speed, quality, accuracy, and reliability.
Deep, current knowledge of the AI tooling and coding-agent ecosystem, such as Claude Code, GitHub Copilot, Cursor, Codex, or similar.
Experience with telemetry, dashboards, and AI usage analytics.
Strong hands-on software engineering experience.
Full-stack capability: backend, APIs, automation, and basic frontend when needed.
Experience building internal tools, developer tools, automation platforms, productivity solutions, CLI tools, internal plugins, developer portals, or internal marketplaces.
Experience integrating with GitHub API, Jira API, Confluence API, and CI/CD systems.
Proficiency in TypeScript, Node.js, Python, React, or similar modern technologies.
Strong product sense and ability to translate engineering pain points into practical tools and solutions.
Ability to design, deliver, and own working solutions independently.
Comfortable working with ambiguity and rapidly evolving technologies.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo and Ra'anana
Job Type: Full Time
we are seeking a Senior Product Manager focused on ML Platform to be a key member of our Product Management team. Join a dynamic and forward-thinking company at the forefront of AI infrastructure. We leverage advanced technologies to develop innovative solutions that drive efficiency, scalability, and exceptional compute performance. Collaborate with the industry's best as we partner with hyperscalers, emerging NeoClouds, and enterprises building large-scale AI clusters, shaping the future of heterogeneous AI infrastructure. Our environment fosters creativity, teamwork, and growth, and offers you the opportunity to make a meaningful impact while working on groundbreaking projects.
As a Senior Product Manager for the ML Platform, you will own the strategy, roadmap, and feature definition of ' heterogeneous inference serving platform - a system designed to enable efficient inference across diverse and mixed compute environments. You will work directly with our R&D teams and end customers to shape the product, engage compute and storage partners to co-define reference architectures, and serve as an internal expert on performance benchmarking and collective communication tuning in support of ' cluster and performance engineering teams.
Requirements:
5+ years of experience in the HPC or AI/ML industry, with deep hands-on technical expertise across the AI compute stack.
Deep understanding of inference serving architectures for heterogeneous compute - including serving engines (vLLM, SGLang, or equivalent), support for mixed accelerator environments, and the scheduling and memory challenges they introduce.
Solid knowledge of multi-node inference, tensor and pipeline parallelism, and the trade-offs involved in scaling large models across heterogeneous GPU and accelerator clusters.
Solid knowledge of KV-cache management and tiering, including disaggregated prefill/decode architectures, CPU/storage offload, and their operational implications at scale.
Experience with performance benchmarking of ML workloads - defining methodologies, running experiments, interpreting throughput/latency/cost trade-offs, and communicating results to both technical and business audiences.
Familiarity with CCL tuning (NCCL, RCCL) and the impact of collective communication configuration on inference and training efficiency across large GPU clusters.
Familiarity with storage systems relevant to ML workloads - including high-throughput distributed file systems (e.g., Lustre, VAST, WekaIO), object storage, and checkpoint/model weight loading strategies under tight latency budgets.
Experience engaging technology partners (compute, storage, silicon vendors) to define joint reference architectures and go-to-market proposals.
Clear written and oral communication skills with the ability to effectively collaborate with executives, engineering teams, and external partners.
Ability to write extensive technical content (white papers, technical briefs, reference architectures) for external audiences with a balance of technical accuracy and clear messaging.
Travel as needed.
This position is open to all candidates.
 
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