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לפני 11 שעות
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Senior Data Scientist to join the team that builds the predictive intelligence powering the app. You will own the ML models behind user engagement, cardiovascular risk stratification, and personalized health recommendations - the systems that determine what users see, when they're nudged, and how their health trajectories are shaped.

This role demands both statistical depth and engineering proficiency - you will be expected to take models from research through to deployment, write code built for production, and use AI coding assistants fluently as part of how you get work done.

Responsibilities
Lead end-to-end development of predictive ML models. From data exploration and feature engineering through training, validation, deployment, and ongoing monitoring across engagement and clinical risk domains.
Apply strong statistical foundations to model design, feature selection, uncertainty quantification, and interpretation of results
Write production-grade Python code that is clean, tested, and built for maintainability and scale.
Use AI coding assistants to accelerate development, code review, and documentation without sacrificing quality or rigor.
Partner with product managers, data engineers, and software engineers to translate strategic questions and user behavior patterns into measurable, data-driven solutions.
Research and implement cutting-edge ML techniques spanning supervised and unsupervised learning, causal inference, deep learning, and reinforcement learning to tackle complex healthcare challenges.
Contribute to MLOps infrastructure: model serving, versioning, evaluation pipelines, and monitoring.
Design and interpret A/B tests and other experimental methodologies to measure the impact of models, features, and interventions.
Requirements:
Qualifications:
5+ years of hands-on experience developing, deploying, and maintaining ML models in production environments.
Bachelor's degree in Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field - a strong statistical foundation is essential for this role.
Deep expertise in statistics and probability: distributions, inference, hypothesis testing, Bayesian methods, causal inference, and experimental design, with the ability to apply these rigorously in a healthcare context.
Strong software engineering skills in Python: production-grade practices, version control, testing, and reproducibility.
Proficiency using AI coding assistants as a core part of the development workflow.
Expertise with ML frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM.
Experience building or working within ML pipelines end-to-end, including feature engineering, model registries, and deployment tooling.
Strong ability to translate complex statistical and technical findings into clear insights and recommendations for both technical and non-technical stakeholders.

Advantage:
Experience with cloud platforms (AWS preferred), containerization (Docker, Kubernetes), and MLOps platforms.
Prior work with healthcare or clinical datasets, including wearable device data, EMR, or claims data.
Experience with recommendation systems, reinforcement learning, or advanced causal inference.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
As a Machine Learning Scientist, you will design, build, and deploy advanced models that guide pricing and promotional optimization across us. You will work closely with other scientists, engineers, analysts, and product teams to translate complex business challenges into scalable, data-driven solutions that deliver measurable impact.

Key Job Responsibilities and Duties:

Develop and deploy models for causal inference, uplift estimation, and optimization to measure and maximize the incremental effect of price and promotion decisions.

Design and improve dynamic pricing algorithms that balance competitiveness, conversion, and profitability.

Contribute to the development of platform capabilities, enhancing experimentation, simulation, and decision-support capabilities.

Partner with product and business stakeholders to translate scientific insights into actionable strategies.

Stay up to date with the latest advances in machine learning, causal modeling, and pricing optimization, and apply them pragmatically at scale.
Requirements:
Qualifications & Skills:

MSc or PhD (or equivalent experience) in a quantitative field such as Computer Science, Statistics, Economics, Operations Research, Mathematics, Engineering, Artificial Intelligence, or Physics.

Relevant professional or academic experience applying Machine Learning to business problems (typically MSc + 5 years, or PhD + 3 years).

Proven track record designing and executing end-to-end research and development projects, and generating measurable impact through large-scale ML model development. Evidence such as peer-reviewed publications, patents, or open-source contributions is a plus.

Advanced knowledge and experience in Causal Inference, Uplift Modeling, Reinforcement Learning, Active Learning, and/or Optimization.

Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, XGBoost).

Experience working with large-scale data systems and production ML pipelines.

Solid understanding of data analytics, A/B testing, and statistical experimentation.

Experience with distributed computing and data technologies such as Spark, Hadoop, Kafka, and SQL.

Familiarity with version control systems and software engineering best practices.

Experience collaborating cross-functionally with developers, analysts, product managers, and UX specialists to deliver machine learning-driven products.

Ability to communicate complex scientific and technical ideas clearly and effectively to both technical and non-technical audiences.

Excellent English communication skills, both written and verbal.
This position is open to all candidates.
 
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22/06/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new AI-based defense techniques against cyber-threats. You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin, shaping the future of cybersecurity and impacting millions of customers.
Key Responsibilities
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.
Requirements:
6+ years of hands-on experience delivering production-grade data science and machine learning projects.
Proven track record in applied data science for cybersecurity.
Deep expertise in probability, statistics, and machine learning, with a proven ability to select, adapt, and apply advanced algorithms to real-world problems.
Proven deep learning experience, including model design, training, and evaluation.
Strong proficiency in Python with solid working knowledge of SQL.
Advanced degree (MSc or PhD) in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a closely related field.
Demonstrated ownership of end-to-end research POCs, from problem formulation and experimental design through execution, analysis, and final recommendations.
Strong emphasis on engineering-quality, production-ready code with high standards for reliability, scalability, and maintainability.
Excellent communication skills, with the ability to clearly articulate complex technical insights to both technical and business stakeholders.
Preferred Qualifications
Direct experience with detection and response platforms (XDR, EDR, or NDR).
Experience working with Big Data platforms (e.g., GCP, BigQuery, Dataflow).
Familiarity with cloud-native architectures and MLOps tools for managing the model lifecycle at scale.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through our companys SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.
This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.
Key Responsibilities
Lead the design, development, and deployment of AI/ML models that enhance our companys security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals.
Requirements:
Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Proven experience building and deploying LLM-based applications and agents (e.g., RAG pipelines, tool-use agents, prompt engineering at scale)
Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
Excellent analytical, problem-solving, and communication skills
Self-motivated, collaborative, and able to work independently
How to Stand Out
Experience with real-time or low-latency AI inference in production environments.
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field.
This position is open to all candidates.
 
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18/06/2026
Location: More than one
Job Type: Full Time
We're looking for a Senior Data Scientist to join the AI cybersecurity team in the Security and Networking Architecture group. As a Senior Data Scientist youll have the opportunity to take an active part in the research and development of our world-class networking and data center security products. This role involves creative problem solving alongside engineering teams, and is key for the continued success of AI networking security.

What youll be doing:

Developing agentic AI systems for security, combining generative models, RAG, and tool-augmented reasoning to automate threat analysis and response workflows.

Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Developing, implementing and improving models and algorithms across media types, whether time series, images, text, audio or video.

Leveraging data pipelines to efficiently process and transform large volumes of data for training and inference purposes.

Applying alignment techniques and parameter efficient fine-tuning to improve model performance.

Measuring and benchmarking model and application performance to drive improvements.

Driving the gathering, building, and annotation of domain specific datasets for benchmarking and training.

Collaborating closely with software and hardware engineers on new features and improvements. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.
Requirements:
What we need to see:

MS/PhD with expertise in Computer Science, Computer Engineering, Electrical Engineering or related field with a focus on Deep Learning or Machine Learning.

5+ years of experience in deep learning and machine learning in a production environment.

Excellent Python programming skills, strong software design fundamentals, and experience leveraging coding agents in development workflows.

Hands-on experience with deep learning development frameworks and libraries (e.g. TensorFlow, PyTorch).

Experience with large scale production systems and pipelines, with a track record of developing production-grade models

Experience with agentic AI systems, agent frameworks, and evaluation of agent performance and reliability.

Strong algorithm development experience, with knowledge of inference optimization techniques such as model distillation, quantization, pruning.

Background with algorithms including zero/few-shot learning, self-supervised and unsupervised learning and generative AI models for synthetic data creation.

Experience with fine-tune / training LLM models

You are proactive, take full ownership of your deliverables, have a can-do approach, and are excited to learn, explore and apply your skills and creativity to some of the most challenging and rewarding problems in the field.


What will make you stand out from the crowd:

Strong software development experience.

Familiarity with GPU based technologies like CUDA, CuDNN and TensorRT.

Experience with tools for data processing and storage.

Security and networking background, with knowledge of security protocols, network architectures, firewalls, intrusion detection systems, and other relevant security and networking concepts.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior Car Insurance Pricing Expert to help shape how we price risk across our global business, from our Tel Aviv office.
This isn't a traditional actuarial role. You'll sit at the intersection of Insurance, Data Science, Product, Engineering, and Business Strategy on our Insurance team, owning hard pricing and risk-management problems end to end. That means finding opportunities, designing better approaches, building scalable tools with technical teams, and turning insights into decisions that move growth, profitability, and risk selection forward.
You might be a trained actuary, a pricing leader, a decision scientist, or a technically strong insurance operator who's built serious pricing capabilities. Formal credentials are a plus, but they're not the point. The point is whether you can use data, insurance intuition, statistical rigor, and AI-enabled tools to solve complex pricing problems better and faster than the industry standard.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Own and evolve core components of Car pricing strategy, bringing analytical rigor and product-minded creativity to how we price risk
Identify high-leverage opportunities across rating, underwriting, segmentation, risk selection, growth, profitability, and portfolio management
Build, evaluate, and improve Car pricing and risk models using actuarial methods, machine learning, AI-enabled workflows, and strong business judgment
Partner with Data Science, Product, Engineering, Finance, and Growth to turn pricing ideas into scalable capabilities
Translate complex pricing problems into clear product and platform requirements, helping teams build internal tools that make better decisions faster
Define and track key metrics - loss ratio, rate adequacy, conversion, retention, segmentation lift, and model performance - to keep decisions grounded in real impact
Make complex actuarial and pricing concepts clear and actionable for technical and non-technical audiences alike, and help build pricing acumen across the Tel Aviv team
Requirements:
8+ years of experience in Car insurance pricing, actuarial science, decision science, risk analytics, or a closely related field
A proven track record solving complex pricing, underwriting, segmentation, or risk-management problems with measurable business impact
Strong analytical instincts - knowing how to find signal in data, make decisions under uncertainty, and separate elegant analysis from useful analysis
Hands-on fluency with modern analytical tools, agentic AI capabilities, and code - including experience using generative AI, coding agents, or advanced automation to materially improve analytical workflows
Solid understanding of Car insurance pricing fundamentals, including rating plans, loss costs, rate adequacy, segmentation, model validation, telematics and financial performance.
Familiarity with predictive modeling methods such as GLMs, gradient boosting, random forests, clustering, and feature engineering
Experience building or modernizing pricing platforms, rating engines, underwriting tools, or internal decision-support software
Product-minded problem solving: the ability to turn a messy workflow, technical constraint, or business problem into a clear, prioritized path forward - with a track record of partnering with Product and Engineering teams to ship production-grade tools
Strong communication skills - you can explain pricing decisions, tradeoffs, and model outputs clearly to executives, engineers, product teams, and regulators
This position is open to all candidates.
 
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לפני 15 שעות
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Data scientist Expert to join us and spread our power. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the platform - from autonomous threat investigation agents to AI-powered security operations workflows
Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
Collaborate with engineering teams to design, build, and maintain production pipelines
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.
Requirements:
WHAT YOULL BRING
An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience
5+ years of experience in leading data science and machine learning projects, with significant hands-on work building LLM-based applications or AI agents
Deep practical experience with LLMs - prompt engineering, fine-tuning, model selection, and understanding trade-offs across providers and model families
Experience with distributed cloud systems - hands-on familiarity with cloud-native architectures at scale
Strong knowledge of deep learning models and common model architecture such as transformer models
Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch)
Ability to work independently in a fast-paced, and come up with creative solutions to challenging problems
Excellent communication (both written and verbal) and presentation skills
Advantage: Knowledge of cybersecurity principles, attack vectors, and defense mechanisms.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
The Data Science role is the engine behind our industry-leading Exposure Management (EM) platform.
You will be responsible for the AI models that power our CAASM (Cyber Asset Attack Surface Management) capabilities and our advanced Vulnerability Prioritization and Remediation engines.

We are building the intelligence layer that helps organizations implement a Continuous Threat Exposure Management (CTEM) framework. You will build models that normalize fragmented data from hundreds of sources, calculate complex risk scores, and prioritize which exposures actually pose a threat to the business.

We are looking for an experienced and creative data scientist, with a software development touch, to join our Data Science and our family. A data scientist that understands and loves data, and lots of it.

What you will do...
Solve Applied Product Challenges: Deep-dive into our product ecosystem to identify and solve high-impact problems. You will translate complex customer needs into scalable ML features that directly improve the user experience.
Lead Exposure Intelligence R&D: Develop features that unify asset data (CAASM) with threat intelligence. This includes building models for entity resolution (deduplicating assets across fragmented sources) and automated risk assessment.
Advanced NLP & Knowledge Extraction: Use NLP and LLMs to parse unstructured security data-such as CVEs, threat intel feeds, and security advisories-to automate the mapping of vulnerabilities to specific business contexts.
Predictive Prioritization: Design and optimize algorithms that go beyond static CVSS scores. You will incorporate exploitability (EPSS), reachability, and business criticality to help clients focus on the 1% of exposures that matter most.
End-to-End Ownership: Work closely with Product Managers and Data analysts and Engineers to ensure your models aren't just accurate in a notebook, but are robust, explainable, and deliver clear value within the product UI.
Graph-Based Attack Surface Mapping: Identify hidden patterns and relationships between assets, users, and vulnerabilities to visualize the potential "blast radius" of a security gap.
Requirements:
Academic Background: M.Sc./PhD in Computer Science, Statistics, Engineering, or a related field (or equivalent high-level professional experience).
Industry Experience: 6+ years in Data Science, with a heavy focus on NLP and solving complex, real-world problems using ML/Deep Learning.
Technical Mastery: Hands-on experience with PyTorch, Hugging Face, scikit-learn, and SQL. Familiarity with processing large-scale datasets (PySpark, or similar) is highly valued.
Domain Awareness: Proven ability to apply statistical modeling to cybersecurity, risk management, or complex system analysis. Experience with Vulnerability Management or Graph Theory is a significant plus.
Product and collaborative Driven Mindset: You are obsessed with understanding the "Why" behind the data. You enjoy learning the nuances of the product and the cybersecurity domain to ensure your DS solutions are highly applicable.
This position is open to all candidates.
 
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1 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a highly skilled Senior Data Scientist to join our dynamic AI team. The ideal candidate blends a strong foundation in machine learning, statistics, and software engineering with a passion for modern, AI-accelerated development. You will be responsible for leading the research, design, and end-to-end development of cutting-edge machine learning systems at scale.
What you'll be doing:
Innovate at Scale: Design and deploy advanced ML solutions by leveraging our vast, large-scale datasets.
Build & Scale: Develop online, scalable models and tools using machine learning, deep learning, NLP, and modern LLM frameworks.
End-to-End Ownership: Drive projects through their entire lifecycle-from translating complex business questions into technical strategies, all the way to robust production deployment.
Production Excellence: Champion high engineering standards by building, monitoring, and optimizing resilient production workflows.
Cross-Functional Collaboration: Work closely alongside data scientists, ML engineers, product managers, analysts, and developers to solve complex, multi-faceted problems.
Requirements:
Education: MSc or PhD in Data Science, Computer Science, Mathematics, Statistics, or a related engineering field.
Experience: 4+ years of proven experience as a Data Scientist solving complex business problems with state-of-the-art algorithms.
Deep Learning: Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
Engineering & Production: High-level software engineering expertise, with a strong track record of deploying, maintaining, and scaling models in rigorous production environments.
Strong analytical thinking: Take a vague business question, translate it into a testable hypothesis, build the infrastructure to run an experiment, and draw rigorous conclusions from the results.
Massive Scale: Experience working with billions of records and big-data frameworks (e.g., Spark, Ray, Dask, Airflow).
Domain Expertise: Proven experience building and optimizing applied recommendation systems.
AI development: Fluency with modern AI coding tools and practices (e.g. Cursor, Claude Code, Copilot) and an eagerness to integrate them into your daily workflow
Leadership & Soft Skills: Demonstrated experience leading machine learning projects. You are a highly analytical team player capable of handling multiple tasks simultaneously in a fast-paced environment.
You might also have:
LLM & Agentic Frameworks: Experience building applications with modern AI tools and frameworks (e.g., LangChain, LangGraph).
AI Observability: Hands-on experience with LLM observability, evaluation, and tracing frameworks (e.g., Langfuse).
MLOps & Infra: Experience working with MLOps tools (e.g., MLflow, Kubeflow, Weights & Biases, SageMaker) and feature stores (e.g., Feast, Tecton).
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Senior Data Scientist.
As a Senior Data Scientist, you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.
Responsibilities:
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards
Requirements:
5+ years in ML roles with demonstrated production impact
Advanced degree (MS/PhD) in a quantitative field, or equivalent industry depth
Deep expertise in mathematical optimization - convex, constrained, and gradient-based methods
Hands-on experience with Bayesian or hyperparameter optimization
Strong causal inference skills - propensity scoring, uplift modeling, or experimental design
Applied ML experience in optimization domains: pricing, bidding, or resource allocation
Advanced time series modeling for dynamic, decision-making systems
Proven experience deploying and monitoring real-time ML models in production
Familiarity with experiment tracking, model versioning, and performance monitoring
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8682838
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09/06/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an Experienced Data Scientist - Data Security.
This role combines hands-on research, large-scale production systems, and close collaboration with engineering teams. The work focuses on solving real-world cybersecurity and data security challenges using modern AI approaches, including document understanding, semantic classification, LLM pipelines, and compound AI systems.
About the Team:
Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for products, and drive innovation and thought leadership in cybersecurity. The team also develops advanced AI-driven capabilities for Data Security use cases, operating at large production scale across enterprise environments.
Key Responsibilities:
Design and develop NLP and LLM-based solutions for document understanding and sensitive data classification.
Drive projects from research and prototyping to production deployment.
Work closely with engineering teams to integrate and promote models within large-scale ML pipelines.
Improve model quality, scalability, latency, and reliability.
Design evaluation and monitoring frameworks for production AI systems.
Ensure AI models are reliable, scalable, and production-ready for enterprise security environments.
Requirements:
5+ years of experience in Data Science / Applied ML, with strong hands-on experience building and deploying NLP and LLM-based solutions in production environments.
Experience in Data Security or Cyber Security is a strong advantage, particularly in areas such as document classification, semantic search, or enterprise data analysis.
Strong Python skills and experience with modern ML/DL frameworks such as PyTorch or TensorFlow, including transformer architectures and fine-tuning workflows.
Experience working with large-scale datasets and production ML systems, including tools such as SQL, Spark, or similar distributed data processing frameworks.
Experience with MLOps, scalable model deployment, inference optimization, CI/CD practices, and the end-to-end ML lifecycle from data preparation to production monitoring.
Experience working closely with software engineering teams in cloud-native environments; familiarity with AWS/Azure/GCP, Kubernetes, and microservices architectures is a plus.
Track record of delivering impactful AI solutions in real-world production settings, with strong communication, collaboration, and independent problem-solving skills.
Ph.D. or M.Sc. in Computer Science, Engineering, Mathematics, or a related quantitative field is a plus, but not required with equivalent industry experience.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8687250
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