Senior AI ML Solution Engineer, AI-Native Development

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8792284

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04/08/2026

Network Solution Verification Engineer

חברה חסויה

Location: Tel Aviv-Yafo and Yokne`am

Job Type: Full Time

We are seeking a Network Solution Verification Engineer to join our R&D organization, focused on validating our customer-facing networking solutions at scale using a state-of-the-art End-to-End (E2E) simulation cluster environment.

In this role, you will be a hands-on technical contributor at the intersection of networking, automation, and AI-driven validation - designing and implementing the simulation frameworks, agentic workflows, and regression pipelines that ensure our networking solutions meet the highest standards of quality and real-world applicability before reaching customers.

What you'll be doing:
Designing and implementing end-to-end validation frameworks for our customer-facing networking solutions at scale, leveraging a dedicated E2E simulation cluster environment.
Writing, maintaining, and extending automated test suites and regression pipelines for networking protocols and large-scale simulation runs, ensuring repeatable, high-confidence validation outcomes.
Performing deep regression analysis on simulation results - identifying failure trends, isolating root causes, and delivering clear, actionable findings to architecture and design teams.
Developing agentic AI flows that autonomously perform regression analysis, detect coverage gaps, generate new test cases, and implement validation code - continuously learning from simulation results and product changes to accelerate coverage without manual intervention.
Integrating validation pipelines into CI/CD workflows to enable continuous, automated regression at scale, working closely with DevOps and platform teams.
Collaborating closely with Design, Architecture, and NCS teams to understand solution requirements, translate them into simulation scenarios, and provide early-cycle quality feedback that influences product direction.
Analyzing customer-reported networking issues, mapping them to simulation coverage gaps, and building targeted test cases that prevent regression.
Continuously exploring new simulation technologies, agentic frameworks, and networking standards to evolve and improve the team's validation methodology.

Requirements:
What we need to see:
B.Sc. degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
3+ years of hands-on experience as a software developer.
Strong proficiency in Python for test automation, tooling development, and pipeline implementation.
Hands-on experience with network simulation or emulation tools (e.g., Containerlab, GNS3, SONiC testbeds, or equivalent platforms).
Proven experience designing and building simulation agents or traffic generators that mimic real-world networking behavior at scale.
Solid experience with agentic AI frameworks and LLM-based automation (e.g., LangChain, LangGraph, AutoGen, or similar) and practical ability to apply them to validation and test generation workflows.
Strong command of regression analysis methodologies - able to triage, classify, and extract actionable conclusions from large-scale test result datasets.
Comfortable operating in a fast-paced, cross-functional, multi-timezone engineering environment with strong verbal and written communication skills.

Ways to stand out from the crowd:
Hands-on experience validating data center networking solutions or hyperscale network environments (spine-leaf, fat-tree, or Clos topologies).
Familiarity with our networking products - BlueField DPUs, ConnectX NICs, Spectrum switches, or the DOCA software stack.
Deep understanding of networking protocols and architectures (e.g., BGP, EVPN, VXLAN, RDMA/RoCE, Ethernet, IP routing, L2/L3 switching).
Hands-on experience building agentic pipelines for automated test generation, result triage, or validation code synthesis - including prompt engineering and tool-use patterns for LLM agents.

This position is open to all candidates.

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8768268

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21/07/2026

Senior Delivery Consultant - AI/ML - Application Development, Professional Services Israel

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking an experienced Senior Delivery Consultant - Modernization with deep expertise in Artificial Intelligence to join AWS Professional Services (ProServe). This role combines strategic architectural vision with hands-on technical leadership to deliver innovative AI solutions that drive customer success and business transformation across diverse industries and use cases.

Key job responsibilities
* Architecture & Design: Design and architect end-to-end AI-powered application solutions aligned with customer business objectives and technical requirements.
* Define application architecture patterns, standards, and best practices for AI/ML integration on AWS.
* Create technical roadmaps for customer AI application development and modernization initiatives
* Evaluate and recommend AWS AI/ML services and technologies including our Bedrock, SageMaker, and generative AI solutions
* Design data pipelines and ETL processes to support AI model training and inference using AWS services
* Customer Engagement & Consulting:
Lead customer engagements from discovery through implementation, serving as trusted technical advisor
* Conduct AI readiness assessments and develop adoption strategies tailored to customer maturity levels
* Facilitate architecture workshops and design sessions with customer stakeholders
* Deliver Well-Architected reviews focused on AI/ML workloads
* Build strong relationships with customer technical teams and executive leadership
* Guide customers in constructing AI processes aligned with AWS best practices
* Technical Leadership: Lead cross-functional teams in implementing AI solutions from concept to production
* Provide technical guidance on AI model integration, deployment strategies, and optimization on AWS
* Conduct architecture reviews ensuring solutions meet scalability, performance, security, and cost-efficiency requirements
* Mentor customer teams and junior ProServe consultants on AI best practices and AWS technologies
* Collaborate with data scientists, ML engineers, and software developers to translate AI models into production applications
* AI Solution Development: Design architectures for generative AI applications including RAG (Retrieval-Augmented Generation) systems, chatbots, and intelligent agents using our Bedrock
* Architect real-time and batch AI inference pipelines with appropriate monitoring and observability
* Implement MLOps practices using SageMaker for model versioning, deployment automation, and continuous improvement
* Design solutions for responsible AI including bias detection, explainability, and governance frameworks
* Optimize AI application performance, cost, and resource utilization across AWS services
Knowledge Sharing & Thought Leadership
* Develop reusable assets, reference architectures, and best practice documentation
* Contribute to AWS ProServe knowledge base and customer-facing content.

דרישות:
Basic Qualifications
- 10+ years of experience in application architecture and software development.
- 5+ years of hands-on experience with AI/ML technologies and frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face).
- Deep expertise in AWS cloud platform with focus on AI/ML services (SageMaker, Bedrock, Comprehend, Rekognition, etc.).
- Proficiency in programming languages such as Python, Java, or similar.
- Strong knowledge of generative AI technologies including LLMs, prompt engineering, fine-tuning, and RAG architectures.
- Understanding of various AI domains: NLP, computer vision, recommendation systems, predictive analytics.
- Willingness to travel to customer sites as needed.

Preferred Qualifications
- AWS Certified Machine Learning Specialty or AI Practitioner or Generative AI - Associate.
- Contributions to open-source AI projects or published research.
- Experience with responsible AI frameworks, governance practices, and compliance requirements.
- Prior experience in ProServe, consulting, or systems integration roles המשרה מיועדת לנשים ולגברים כאחד.

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8748479

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04/08/2026

Network Solution Verification Manager

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Network Solution Verification Manager to join our R&D organization, leading the validation of our customer-facing networking solutions at scale using a state-of-the-art End-to-End (E2E) simulation cluster environment.

In this role, you will build and lead a team of validation engineers, owning the strategy, methodology, and execution of simulation-based validation frameworks that ensure our networking solutions meet the highest standards of quality, scale, and real-world applicability before reaching customers.

What you'll be doing:
Leading and managing a team of network validation engineers responsible for end-to-end validation of our customer-facing networking solutions at scale, using a dedicated E2E simulation cluster environment.
Defining the overall validation strategy and roadmap - establishing simulation methodologies, test coverage frameworks, and quality gates that align with product milestones and customer use cases.
Pioneering the use of agentic AI flows within the validation organization - leading the team to design, build, and operate AI-driven agents capable of autonomously performing regression analysis, identifying coverage gaps, generating new test cases, and implementing validation code. These agentic workflows will continuously learn from simulation results and product changes, dramatically accelerating the team's ability to scale test coverage and respond to emerging quality signals without manual intervention.
Overseeing the design and continuous improvement of automated regression suites for networking protocols and large-scale simulation runs, ensuring scalable, repeatable, and high-confidence validation outcomes.
Establishing a rigorous regression analysis culture - guiding the team in identifying trends, root causes, and systemic coverage gaps, and ensuring timely resolution in collaboration with engineering stakeholders.
Serving as the primary validation partner to Design, Architecture, and NCS teams - translating solution requirements into simulation scenarios, providing early-cycle quality feedback, and influencing product direction.
Analyzing customer-reported networking solution issues, driving test gap analysis, and ensuring robust regression coverage that prevents recurrence.
Staying current with emerging networking standards, simulation technologies, and industry best practices to continuously evolve the team's validation capabilities.

דרישות:
What we need to see:
B.Sc. degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
3+ years of experience in a leadership or management role, leading software or hardware validation/test engineering teams.
7+ years of overall experience in network validation, network testing, or systems verification.
Proven track record of building and executing test automation strategies for network or distributed systems at scale, with hands-on background in Python-based automation.
Strong understanding of regression analysis methodologies - ability to drive actionable conclusions from large-scale test result datasets and translate them into engineering improvements.
Demonstrated ability to collaborate cross-functionally with architecture, design, and product teams in a fast-paced, multi-timezone environment.
Strong verbal and written communication skills, with experience presenting validation strategies and quality metrics to senior leadership.

Ways to stand out from the crowd:
Deep understanding of networking protocols and architectures (e.g., BGP, EVPN, VXLAN, RDMA/RoCE, Ethernet, IP routing, L2/L3 switching).
Experience with network simulation or emulation environments (e.g., Containerlab, GNS3, SONiC testbeds, or equivalent platforms) and the ability to guide teams in leveraging them effectively.
Experience managing validation of data center networking solutions or hyperscale network environments (spine-leaf, fat-tree, or Clos top#EN המשרה מיועדת לנשים ולגברים כאחד.

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8768267

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חברת השמה / כח אדם

28/07/2026

Applied AI Scientist - On Site

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a hands-on Applied AI Scientist to join our core R&D team and drive the development of next-generation AI systems for autonomous driving. This role sits at the intersection of applied research and deployment. This role sits at the intersection of applied research and deployment. You will work directly on our multi-layered autonomy architecture, with a primary focus on real-time predictive models for driving decisions. A deep technical role for someone who thrives on turning cutting-edge research into real, working systems under hard constraints.

Responsibilities:
Own the research-to-deployment cycle for driving models - from literature review and prototyping through to production integration.
Design, implement, and iterate on real-time predictive models, including vision-language-action (VLA) models.
Collaborate on reasoning systems, contributing to VLA models that handle planning across varied horizons.
Bridge cloud-scale training with edge deployment - work on model compression, quantization, speculative decoding, and efficient inference for embedded automotive platforms.
Evaluate and integrate state-of-the-art techniques from the broader AI research community into our autonomy stack.
Collaborate closely with internal R&D teams to unblock technical challenges, accelerate delivery, and raise the overall technical bar.

Requirements:
Requirements:
Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related field (an MSc with an exceptional background will also be considered).
Strong publication or deployment track record in one or more of: deep learning, computer vision, generative AI, reinforcement learning, or motion prediction.
Demonstrated ability to go from paper to working implementation - not just theory, but shipped systems.
Strong coding skills in Python; experience with C++ is a plus.
Familiarity with modern ML infrastructure: PyTorch, ONNX, Triton, Dynamo, distributed training, model optimization.
Solid mathematical foundations in probability, optimization, and statistics.

Attributes:
Experience with CUDA or low-level GPU optimization.
Hands-on work with model quantization, distillation, or efficient inference on edge devices.
Background in real-time, safety-critical, or embodied AI systems (robotics, autonomous vehicles, drones, etc.).
Experience with foundation models (Language, Vision, Tabular, VLAs) and their on-device deployment.
Familiarity with driving datasets, simulation environments, or sensor fusion pipelines.

This position is open to all candidates.

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8757491

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חברת השמה / כח אדם

13/08/2026

Principal/Senior ML Platform Engineer (Cortex)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

Requirements:
Core Engineering: 4+ years experience as a Senior ML Engineer, MLOps Engineer, or Backend Platform Engineer (Hands-On) working with cloud environments.
Model Lifecycle Engineering: Hands-on experience managing the technical lifecycle of diverse model architectures, spanning classic ML, LLMs/SLMs, and agentic/RAG systems. This includes engineering scalable data preparation and processing pipelines as well as implementing infrastructure for model training, fine-tuning, optimization, and high-throughput production serving.
Distributed Training & Compute: Strong foundational knowledge of Deep Learning concepts (neural network architectures, training dynamics, optimization techniques) paired with proven experience setting up and optimizing distributed training workloads across multiple GPUs (using PyTorch, DeepSpeed, Megatron-LM, or cloud-native training infrastructure).
Cloud & Infrastructure Architecture: Strong infrastructure knowledge within a major cloud provider ecosystem (GCP, AWS, or Azure), specifically leveraging managed AI platforms and services.
Python Expertise: Expert-level Python skills focused on ML infrastructure, pipelines, and automation frameworks.
CI/CD Integration: Experience with modern CI/CD patterns (such as GitLab CI or GitHub Actions) for automating software and model delivery loops.
AI Tooling & Development: Proficient in leveraging day-to-day AI tools and ecosystems (e.g., Claude, Gemini, MCPs, custom skills, and markdown formatting) to generate, review, and test code dynamically within your development cycle.
Preferred Qualifications
Strong GCP ecosystem experience.
Background in data science or deep learning workflows.
Cybersecurity domain knowledge.

This position is open to all candidates.

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8781454

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1 ימים

Machine Learning Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

What You'll Do
- Design and ship the ML backbone of Gini AI Workers - routing, tool selection, reasoning, memory, evaluation.
- Build evaluation and feedback loops - offline evals, online A/B, regression harnesses, human-in-the-loop labeling pipelines.
- Optimize cost and latency across the agent stack: prompt engineering, model routing (frontier ↔ small ↔ fine-tuned), caching, speculative decoding, distillation.
- Fine-tune and/or RAG-tune models for vertical enterprise tasks (invoice extraction, PO matching, ticket triage, forecasting).
- Own the ML infra - training pipelines, experiment tracking, model registry, deployment, monitoring, drift detection.
- Partner with backend + product to turn research into shipped features on a weekly cadence.

Requirements:
- 4+ years of ML engineering in production (not just research or notebooks).
- Hands-on LLM experience in 2025-2026: agentic systems, tool-use, function-calling, RAG, structured output, eval design.
- Strong Python. Comfortable with PyTorch/JAX and one serving stack (vLLM, TGI, TensorRT-LLM, SageMaker, or similar).
- You've built an eval pipeline that actually caught a regression in prod.
- You read the papers and know which ones to ignore.
Nice to Have
- Experience with MCP, LangGraph, DSPy, or custom agent frameworks.
- Fine-tuning (LoRA/QLoRA, DPO/ORPO, RLAIF) on open-weight models (Llama, Qwen, Mistral, DeepSeek).
- Vector DBs (pgvector, Pinecone, Weaviate, Qdrant), reranking, hybrid retrieval.
- Prior work on multi-agent systems or enterprise copilots.

This position is open to all candidates.

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8798773

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11/08/2026

ML Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are seeking an experienced and visionary ML Engineer to join our dynamic technology organization. The successful candidate will be a part of a team of talented AI Engineers, Building agentic AI solutions, driving innovation and delivering business value through advanced Generative AI solutions & machine learning techniques. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge Gen AI and LLM methodologies and a passion for continuous learning and development.

Responsibilities

Build the solution: Own end-to-end technical delivery of agentic systems, from source-system integration through agent design, development, evaluation, and production deployment.
Integrate AI systems with source systems (Salesforce, Databricks, Splunk, internal APIs, business applications). Handle agent harness and orchestration.
Handle the operational handover to the business function and any necessary support transition.
Collaborate across teams: Partner closely with data engineering, platform, security, and business teams to align on requirements, dependencies, and integration points.
Engage stakeholders: Gather requirements directly from business functions, communicate technical trade-offs clearly, and keep stakeholders informed on progress, risks, and timelines.
Uphold quality and reliability: Establish and maintain best practices for code quality, testing, evaluation, monitoring, and observability of deployed AI systems.
Contribute to the team's technical growth through knowledge-sharing and help shape engineering standards and reusable patterns.
Stay current: Continuously evaluate emerging Gen AI, LLM, and agentic frameworks, and recommend tools and approaches that improve delivery speed and solution quality.

Requirements:
5+ years of ML / AI engineering, with at least 2 years building production AI / Agentic systems.
Hands-on with at least one Agentic framework (LangGraph, CrewAI, or custom) and an LLM provider's production tooling APIs.
Fluency in Python.
Track record of shipping fast: has examples of taking an AI system from idea to production in weeks, not quarters
Comfortable working directly with business stakeholders without a product manager intermediary on every interaction

This position is open to all candidates.

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8777797

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09/08/2026

Senior Data Platform Software Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a highly skilled Data Platform SW Engineer to join the Applied Networking AI group. In this role you will help develop advanced data acquisition solutions for the fields of predictive-maintenance, root-cause analysis and AIOPS. You'll collaborate closely with subject-matter-experts (SMEs), applied-researchers, architects, data-engineers and other stakeholders to push the envelope forward in using cutting-edge technologies and data-driven insights to improve our products.

As a key contributor you will develop and own metric-extraction, measurement and telemetry tools that enable a high resolution viewpoint into the hardware. You will experiment and iterate fast and in collaboration with applied-researchers to improve our ML diagnostic and prediction toolkit.

What you'll be doing:

Lead the development of advanced metric and measurement tools for real-time data collection and processing, to enable a high resolution viewpoint into the full set of HW components that compose our AI factory solutions (GPUs, networking interfaces, etc).

Work alongside applied-researchers to experiment and iterate on the bridge between metrics and ML.

Partner with architects and product managers to gain a deep understanding of our hardware and roadmap.

Collaborate with data-engineers to enable high resolution tools at scale.

Requirements:
What we need to see:

BSc in Computer Science, Electrical Engineering, Computer Engineering, or equivalent practical experience.

5+ years of hands-on experience demonstrating deep system knowledge and metric extraction development.

Strong understanding of networking, hardware/software systems, performance behavior, or failure analysis.

Solid understanding of AI/ML modeling and statistics.

Excellent ability to convey and communicate data-based insights to stakeholders and management.

Ways to stand out from the crowd:

Experience diagnosing or debugging modern AI hardware.

High energy and a positive, proactive and curious approach.

This position is open to all candidates.

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8773685

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אירעה שגיאה בשליחת פרטיך למשרה

19/07/2026

ML Engineering Team Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're looking for an experienced and passionate ML Engineering Team Lead to lead our ML Engineering team and shape the next generation of our AI infrastructure. This is a hands-on leadership role where you'll combine technical leadership, software architecture, and people management to build scalable, production-ready AI systems running on edge devices.
About The Role:
Lead, mentor, recruit, and grow a team of software engineers, fostering a culture of ownership, collaboration, and continuous improvement.
Own the team's technical roadmap, architecture, execution, and project prioritization, aligning delivery with business goals.
Design, build, and maintain scalable software and ML infrastructure across cloud and edge environments.
Partner with AI Researchers to productionize Computer Vision and Deep Learning models into reliable, high-performance systems.
Design and optimize inference pipelines with a focus on scalability, latency, and reliability.
Drive engineering excellence through architecture reviews, code reviews, development best practices, and modern AI-assisted engineering workflows.

Requirements:
6+ years of software development experience, including 3+ years leading software engineering or ML engineering teams.
Strong hands-on experience with Python and C++ or Rust.
Experience building, deploying, and maintaining production-grade Machine Learning systems.
Strong understanding of software architecture, scalable system design, and performance optimization.
Experience collaborating with AI, Machine Learning, or Computer Vision teams.
Excellent leadership, communication, and organizational skills, with a strong ownership mindset.
Experience using modern AI-assisted development tools (such as Cursor, Claude Code, or Codex) while maintaining high engineering quality.
Nice to Have:
Hands-on experience developing and optimizing AI applications on NVIDIA edge platforms, particularly NVIDIA Jetson devices, including GPU acceleration and deployment on resource-constrained systems.
Experience with modern AI and Computer Vision frameworks such as PyTorch, CUDA, TensorRT, NVIDIA DeepStream, and GStreamer.
Experience with containerized and cloud-native development using Docker, Kubernetes, and CI/CD pipelines.
Experience using agentic AI coding tools (such as Cursor, Claude Code, Codex, or similar) as part of the software development lifecycle to improve engineering productivity while maintaining code quality and best practices.

This position is open to all candidates.

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