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לפני 9 שעות
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 our 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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Location: Tel Aviv-Yafo
Job Type: Full Time
As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.

Key Job Responsibilities and Duties:

Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.

Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.

Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.

Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.

Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.
Requirements:
Role Qualifications and Requirements:

We are looking for driven MLEs who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right mindset and tools.

We have found that people who match the following requirements are the ones who fit us best:

Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.

Minimum of 4 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions.

Strong programming skills in languages such as Python and Java.

Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.

Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks.

Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

Deep understanding of machine learning algorithms, statistical models, and data structures.

Experience in deploying large-scale language models like GPT, BERT, or similar architectures - an advantage.

Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.

Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.

Experience of working on products that impact a large customer base - an advantage.

Excellent communication in English; written and spoken.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.


Key Job Responsibilities and Duties:

Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.

Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.

Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.

Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.

Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.
Requirements:
Qualifications & Skills:

Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.

Minimum of 6 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions.

Strong programming skills in languages such as Python and Java.

Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.

Experience with LLMs, Agents and MCP in production environments.

Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks.

Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

Deep understanding of machine learning algorithms, statistical models, and data structures.

Experience in deploying large-scale language models like GPT, BERT, or similar architectures - an advantage.

Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.

Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.

Experience of working on products that impact a large customer base - an advantage.

Excellent communication in English; written and spoken.
This position is open to all candidates.
 
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7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.
Requirements:
Proven experience designing and building complex AI systems that have been successfully delivered to production, with an end-to-end understanding of research, architecture, validation, and production handoff.
Strong hands-on experience with modern AI approaches, including Machine Learning, Deep Learning, and LLM-based systems; experience with agentic AI systems or orchestration patterns is a strong advantage.
Demonstrated ability to move quickly from idea to working prototype, with a strong passion for hands-on experimentation and applied innovation.
Experience working in environments involving sensitive data and regulatory constraints, with an understanding of how these considerations shape AI system design.
Excellent system-level technical judgment, including the ability to identify risks, tradeoffs, and unintended consequences in AI systems.
Proven ability to act as a technical leader without formal authority, influencing and guiding senior peers through collaboration and expertise.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to diverse stakeholders.
Ability to contribute to clear technical and AI-related compliance documentation.
High proficiency in Python and modern AI/ML tooling.
Optional / Nice-to-Have :
Deep experience in NLP, NLU, or clinical text processing.
Experience deploying LLMs or agent-based systems in production.
Familiarity with cloud-native ML stacks (AWS, Docker, Kubernetes).
This position is open to all candidates.
 
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לפני 9 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.
Requirements:
What You Bring
5+ years of hands-on work in machine learning / deep learning, including 3+ years focused on NLP / language models.
Proven track record of training and fine-tuning transformer-based models (BERT-style, encoder-decoder, or LLMs), not just consuming hosted APIs.
Strong programming skills in Python and at least one major deep learning framework (PyTorch preferred; TensorFlow).
Solid understanding of transformer architectures, attention mechanisms, tokenization, positional encodings, and modern training techniques.
Experience building data pipelines and tools for large-scale text / log / code processing (e.g. Spark, Beam, Dask, or equivalent frameworks).
Practical experience with ML infrastructure, such as experiment tracking (Weights & Biases, MLflow or similar), job orchestration (Airflow, Argo, Kubeflow, SageMaker, etc.), and distributed training on multi-GPU systems.
Strong software engineering practices: version control, code review, testing, CI/CD, and documentation.
Ability to own research and engineering projects end-to-end: from idea, through prototype and controlled experiments, to models ready for integration by product and platform teams.
Good communication skills and the ability to work closely with non-ML stakeholders (security experts, product managers, engineers).
This position is open to all candidates.
 
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07/06/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.
This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.
Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.
This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.
Responsibilities:
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes
Work closely with product and engineering teams to translate business needs into scalable AI solutions
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact
Requirements:
6+ years of experience in software engineering, machine learning, data science, or related technical roles
3+ years of hands-on experience building machine learning or AI systems in production
Strong experience working with textual data and NLP techniques such as embeddings, classification, semantic search, or information extraction
Hands-on experience building applications powered by LLMs (e.g., prompt pipelines, RAG systems, agents, or structured extraction)
Comfortable leveraging AI-powered developer tools (e.g., Cursor, Claude Code, Copilot, ChatGPT) to accelerate development and experimentation
Strong product intuition - you focus on solving real user problems, not just building models
Excellent collaboration and communication skills
Degree in Computer Science, Engineering, or a related technical field - or equivalent practical experience
This position is open to all candidates.
 
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27/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking for a talented AI/ML developer with strong focus on Python expertise and hands-on experience in AI/ML models to join our Data Science group. The Data Science group plays a pivotal role in driving the execution and delivery of advanced AI and modern Machine Learning solutions, that empower impactful projects to our target sectors.
Key Responsibilities:
Take part in all development aspects, from concept to production, of AI/ML models and LLM-based features (agents development)
Stay up to date with state-of-the-art research in the field of LLM and apply relevant advancements to improve our solutions
Mentor new team members and share your expertise to strengthen the teams collective knowledge
Requirements:
4 years in Data Science, with industry experience in building and optimize AI/ML models
Specialized expertise in modern machine learning methods related to Natural Languages Processing (Transformers, Embeddings, LLMs)
Experience deploying AI/ML services and applications on at least one major cloud platform (Azure, AWS, GCP)
Pratrical skills using modern ML and Generative AI frameworks (Langchain, PyTorch, Tensorflow, Hugging Face and other open-source/ APIs and similar)
Experience with LLM applications and techniques, such as Retrieval-Augmented-Generation (RAG), Chane-of-Thought (CoT) prompting, and open-source LLMs fine tuning
Ability to write production ready code, with strong expertise in designing and implementing ML pipelines
Excellent problem-solving skills with a critical and creative mindset
Exceptional communication skills and a collaborative approach to teamwork
BSc, master or PhD in appropiate technology field (Computer Science, Electrical Engineering, Statistics, Applied Math, etc.)
A Big Plus If You Have:
Extensive experience in integrating and working with vector databases (e.g. Elastic, Milvus and more) for high-performance similarity search, semantic search and embeddings management.
Experience with building continuous integration and monitoring for Machine Learning applications.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
As a Machine Learning Engineering Manager, you will lead a team focused on the foundational ML & Data layers to power the ranking & recommendation systems in scope. You will drive the development of robust data & ML pipelines at scale, lead the implementation of the tools for ML scientists to test and productionize advanced ML RecSys solutions.

As a technical manager of Machine Learning Engineers and Data engineers, you should be passionate about technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML and platforms roadmap, and not be afraid to get your hands dirty with code when needed.

You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.

When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.

Key Job Responsibilities and Duties:

Lead and develop a high-performing team, fostering individual growth and collaboration.

Manage and mentor ML engineers and Data engineers, ensuring their professional development and effectiveness.

Develop scalable ML infrastructure and pipelines for efficient data processing and evaluations deployment.

Evaluate architecture solutions based on cost, business needs, and emerging technologies.

Collaborate closely with software engineers to ensure seamless deployment and model inference.

Monitor application health, set and track relevant metrics, and implement effective maintenance strategies.

Collaborate with stakeholders to translate business requirements into viable ML solutions.

Evaluate and integrate new ML technologies to enhance productivity and performance.

Job ID: 20153.
דרישות:
Qualifications & Skills:

3+ years leading an ML engineering team of a minimum of 4 people in a fast-paced production environment.

Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience), involved in the application of Machine Learning to business problems.

Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).

Strong knowledge in areas like e.g. Recommender Systems, Deep Learning, Information Retrieval, Causal Inference, scaling ML models, etc.

Experience designing and executing end-to-end solutions for deploying different ML models.

Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.

Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

Deep understanding of machine learning algorithms, statistical models, and data structures.

Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).

Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.

Excellent English communication skills, both written and verbal.

Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels

Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team perf המשרה מיועדת לנשים ולגברים כאחד.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
As a Senior Machine Learning Scientist, you will work closely with engineers and product to design, develop, evaluate and deploy Gen AI powered solutions for scalable, customer-facing applications. Your work will focus on applying state-of-the-art agentic capabilities and driving business impact based on rigorous evaluations and experimentation.



Key Job Responsibilities and Duties:

Design end-to-end agentic systems, delivering high-quality, performant, and efficient solutions to production

Build agentic solutions for different tasks and use cases using state-of-the-art techniques

Develop and carry out evaluation strategies, including formulating new metrics and building evaluation judges

Pioneer and promote best practices and adoption of new technology in GenAI application development

Lead and mentor other team members, providing technical guidance and timely feedback to develop the team and motivate them to achieve their goals.

Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into ML solutions.

Conduct deep data analysis to evaluate model performance, label quality, features exploration.

Work closely with ML engineers to ensure and improve the solutions latency/throughput meets product requirements and ensure deployment of your model to production.
Requirements:
Qualifications & Skills:

Bachelors or masters degree in Computer Science, Engineering, Statistics, or a related field.

Minimum of 6 years of experience as a Machine Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions to production.

Advanced knowledge and experience in GenerativeAI models at scale, Natural Language Processing and engineering aspects of developing ML.

Experience designing and executing end-to-end research and development plans and generating impact through large-scale ML & Agentic System development.

Experience on multiple ML facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.

Experience collaborating cross-functionally in the development of ML products (e.g. Developers, Product Managers, UX specialists, etc.).

Strong working knowledge of Python, LangChain, SQL, and Spark or similar technologies.

Strong coding practices, including writing and reviewing production-quality, maintainable, and well-tested code, with the ability to effectively leverage modern AI coding assistants while maintaining high standards for correctness, readability, and system design.

Excellent English communication and presentation skills, both written and verbal.

Successfully driving technical, business and people related initiatives that improve productivity, performance, and quality while communicating with stakeholders at all levels

Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
07/06/2026
Location: Tel Aviv-Yafo and Netanya
Job Type: Full Time
Required Professional Services DevOps Architect
Were reinventing DevOps to help the worlds greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust us to manage, accelerate, and secure their software delivery from code to production -- a concept we call liquid software. Wouldn't it be amazing if you could join us in our journey?
If you love working with brilliant people, being part of an energetic team, changing the world of software and youve got the technical skills, you might be the perfect Frog to join our Swamp! Come and join the Professional Services team and help us to continue to lead the rapidly evolving space of DevOps and DevSecOps!
As a Post Sale DevOps Architect you will...
Responsible for the detailed design of our related projects from inception through production support and the creation of the customer statement of work (SOW) and detailed documentation
Ability to provide technical expertise and consultative advice during all stages of customer engagement
Ensure that the deliverable accurately meets the defined expectations of the customer
Coordinate and oversee functional implementation activities for internal and partner consultants, developers, and customer points of contact on large scale enterprise projects
Mentor PS and partner consultants providing guidance regarding Best Practices, communication, and implementation strategies including collateral in the form of documentation, delivery kits, and training materials
Liaise with and support of other functional groups within - including (but not limited to) training, SolEng, support, product, engineering
Develop case studies, presentations, design documentation, best-practice methodologies and internal process development
Stay up to date on new features, and fixes within the Quarterly product releases and disseminate key information to the PS team
Demonstrate progressive leadership in the full life cycle of the software development environment.
Requirements:
10+ years of experience with Continuous Integration tools: CI Server, Git, Artifactory, Jenkins, Maven, Docker, NPM
Ability to architect and build software delivery pipelines with Docker, npm, Java, Pypi etc.. with various DevOps tools such as Git, Binary repositories management, Binary scanning, and Continuous integration
Good understanding of infrastructure & operations - storage, network, computer, security, cloud (public, on-prem).
Experience with Continuous Deployment and Delivery tools: Chef, Puppet, Ansible, Kubernetes
Hands-on experience in Linux - Mandatory
Hands-on experience with cloud infrastructure - AWS / Azure / GCP - Mandatory
Experience with customer facing with great interpersonal and customer service oriented skills
Experience with server side software on-premise and in the cloud
Experience with Software Architecture design and product development a plus
Experience with MLOps & AI toolset & ecosystem is a plus
5+ years of experience working in professional services or consulting with enterprise customers
Uncompromising will to learn
Open Source state-of-mind.
This position is open to all candidates.
 
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תודה על שיתוף הפעולה
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Location: Tel Aviv-Yafo and Haifa
Job Type: Full Time
Required Machine Learning Hardware Architect, Hardware, Software Co-Design, Cloud
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Tel Aviv, Israel; Haifa, Israel.
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Machine Learning Hardware Architect within the Co-design team, you will serve as a technical lead bridging model architecture innovation and next-generation hardware design. Operating at the highest levels of AI research and engineering, you will define the goal and architectural roadmap for our future machine learning serving and training capabilities. You will guide the integration of ML research such as massive-scale foundation models with advanced silicon architectures to create industry-leading, high-performance, and power-efficient accelerators.
Responsibilities
Define and drive the technical roadmap and architecture for the hardware/software stack to ensure exceptional performance for ML models. Act as the technical liaison across research, software, and hardware teams, steering model architecture innovation to maximize scaling, quality, and hardware efficiency.
Architect next-generation configurable simulation frameworks and performance models, setting the organizational standard for evaluating complex microarchitectural decisions. Drive high-stakes choices regarding Power, Performance, Area (PPA) and buildability for future chip and system architectures, expertly balancing long-term technological trends with strict product delivery timelines.
Guide system-level performance analysis across highly distributed ML systems, innovating new methodologies to optimize and balance compute, memory bandwidth, and inter-chip network requirements. Their leadership will directly shape the future of high-performance AI infrastructure and hardware-software co-design.
Manage cross-functional partnerships across hardware, compiler development and ML teams.
Requirements:
Minimum qualifications:
Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
12 years of experience in computer architecture, chip architecture, or hardware-software co-design.
Experience architecting and developing software systems in C++ or Python for performance modeling, simulation, or system analysis.
Preferred qualifications:
Masters degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science with an emphasis on computer architecture.
Experience as a lead architect managing multi-generational hardware solutions or performance optimizations for massive-scale ML training and inference.
Experience in semiconductor technologies, industry trends, and the future trajectory of process, memory, interconnects, and packaging.
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and deep understanding of their underlying execution models.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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