לוח משרות דרושים NLP/Machine Learning

Are you a Masters or PhD student interested in a 2026 Internship in Data Science? If so, we want to hear from you!

We are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment and is comfortable owning data to drive step-change innovation in the EMEA region or worldwide.

As a Data Science Intern, you will have the following key job responsibilities:
Work closely with scientists and engineers to develop new algorithms to implement scientific solutions for our problems.
Design, run, and analyze A/B tests.
Work on an interdisciplinary team on customer-obsessed research.
Experience our customer-focused culture.
Create and deliver projects that can be quickly applied starting locally and scaled to EMEA/worldwide.
Create and share data with audiences of varying levels technical papers and presentations.
Define metrics and design algorithms to estimate customer satisfaction and engagement.

We are looking for a Senior Machine Learning Algorithm Engineer who is passionate about solving complex, real-world problems at the intersection of hardware and software.
Location: Haifa \ Tel-Aviv in hybrid model.
Responsibilities
Develop advanced ML algorithms using data from our Agents embedded in silicon. Example domains include:
Lifetime predictions
Clustering and dimensionality reduction
Parametric modeling and screening
Time-series forecasting
Lead end-to-end algorithm lifecycle: ideation → research → POC → design → implementation → validation → deployment.
Collaborate closely with cross-functional teams and directly with customers to continuously refine and enhance deployed solutions.
Drive integration of AI-enhanced tools and intelligent pipelines into ML workflows.

We are seeking a Machine Learning expert to join our wireless FW software group and explore innovative applications of ML algorithms in embedded wireless systems and protocols. This role focuses on cutting-edge research to integrate machine learning into wireless firmware architectures as well as protocol design, validation, and performance optimization. The position emphasizes experimental research, algorithm development, and proof-of-concept implementations in the wireless FW domain. This role offers the opportunity to develop novel solutions that bridge the gap between theoretical machine learning capabilities and practical wireless system implementations.
Responsibilities:
Research & Development: Design, develop, and evaluate machine learning algorithms optimized for real-time wireless communication systems operating under strict real-time, power and computational constraints.
Protocol Innovation: Create novel wireless protocols that intelligently incorporate ML techniques for enhanced performance, efficiency, and adaptability.
Algorithm Optimization: Adapt existing wireless algorithms (e.g. Link Quality, QoS, Scheduling etc) by integrating ML approaches while maintaining real-time performance requirements.
Data Collection & Analysis: Gather, analyze, and curate statistics from existing wireless devices and networks to enable ML model training and validation. Design and implement data collection frameworks for various wireless environments and use cases.
System Integration: Develop lightweight ML models suitable for deployment on resource-constrained wireless devices, including edge computing scenarios.
Performance Analysis: Conduct comprehensive performance evaluations through simulation, theoretical analysis, and experimental validation.
Research Publication: Publish findings in top-tier conferences and journals, and present research at industry conferences.
Collaboration: Work closely with hardware engineers, system architects, and product teams to ensure research translates into practical solutions.
Technology Scouting: Stay current with emerging trends in ML, wireless communications, and edge computing technologies.

we are looking for a Data science Team Lead.
As the Data Science Team Lead, you will lead a talented team of data scientists and ML engineers building the infrastructure, systems, and workflows for designing, training, evaluating, and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.
This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving, customer-specific model tuning, offline AI evaluations, and scalable ML systems in a production-grade SaaS environment.
If you are passionate about applied machine learning, fraud detection, and building intelligent systems at scale - we want you on our team.
What youl do:
Lead and mentor a team of Data Scientists and ML Engineers focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.

Join our growing AI team as an Algorithm Developer and help build systems that solve complex challenges in the worlds of creative and marketing. You'll work hands-on across the stack of our AI features and have real impact on the products evolution.



Key responsibilities

Research, design, and implement state-of-the-art algorithms in Generative AI.
Work closely with researchers & engineers to bring prototypes into production.
Optimize algorithms for scalability, cost, and performance in cloud environments.
Collaborate with product teams to translate business needs into algorithmic solutions.

we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of Machine Learning, GenAI, and computer vision within the automotive sector.
With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply Embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.
We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of UVeyes inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges.
A day in the life and how youll make an impact:
* Design and Development of novel, robust and efficient Machine Learning / Deep Learning algorithms for major Vision challenges.
* Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems.
* Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data -centric AI methodologies (active learning, data curation).
* Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for Real-Time inference constraints (on Edge/Cloud devices).

We are looking for a visionary AI Lead to build our internal AI platform and architect adaptive intelligence systems that serve as a dedicated security architect for each of our customers. You will lead a team of AI Researchers and Engineers to move beyond simple integrations and build true autonomous security solutions.
What You Will Build
Autonomous Workflows: Build agents that execute security workflows end-to-end, automating detection, investigation, and response processes.
Runtime Defense: Productize research into active runtime guardrails and defensive control mechanisms.
Internal AI Platform: Build the shared infrastructure for models, training, and evaluations to enable safe, scalable AI features across the organization.
Adaptive Intelligence: Oversee the development of models that learn from customer-specific environments to generate high-signal, personalized insights.
Responsibilities
Lead the AI Research Group, managing AI Researchers, Engineers, and DevOps.
Own the intelligence engine end-to-end, delivering next-generation analytics and contextual visualization features.
Drive the strategic "build vs. partner vs. buy" decisions for cloud prevention and AI controls.
Collaborate with the Threat Team to develop AI-driven threat detections against emerging attack vectors and novel AI threats.

We are looking for a Senior AI Researcher to work closely with our delivery team, translating real-world clinical and scientific questions into rigorous AI and machine learning solutions. In this role, you will lead the development of methodologies, models, and benchmarking frameworks that address complex clinical problems using our unique immune-cell data. Your work will directly impact how our partners understand biology, evaluate hypotheses, and make decisions.

Location: Ramat Gan (hybrid model).

What will you do?
Partner with the collaborations team and scientists to frame complex clinical and biological questions as well-defined data science and modeling problems.
Design, implement, and evaluate the right analytical and modeling approaches for each problem, including robust benchmarking and validation strategies.
Clearly communicate results, limitations, and tradeoffs to internal teams and external partners, enabling confident, data-driven decisions.
Establish best practices for rigor, reproducibility, evaluation, and documentation across delivery-focused data science work.
Work hand-in-hand with immunologists, computational biologists, AI scientists, and engineers to ensure solutions are scientifically sound and production-aware.
Translate modeling solutions into engineered and iterable products used by the internal collaborations team.

we are seeking an experienced and visionary Head of Research to lead, shape, and advance the future of AI innovation across the organization. In this role, you will own the research strategy end-to-end - from long-term roadmap design to hands-on exploration, and guide a multidisciplinary team of NLP research engineers and linguists toward breakthroughs that elevate our core medical coding engine.

You will play a key role in the company, balancing exploratory research with high-impact product delivery. You will partner with Product, Engineering, and executive stakeholders to identify strategic opportunities, drive prioritization, and translate research capabilities into real-world outcomes at scale.

Responsibilities:

Manage and mentor a multidisciplinary research team while driving both technical excellence and personal growth.
Define the long-term research roadmap aligned with product and business objectives.
Lead the full research lifecycle, from ideation and feasibility studies to experimentation, evaluation methods, and production-ready delivery.
Evaluate and introduce new research capabilities and emerging trends such as LLM-based reasoning, semantic/graph modeling, hybrid rule-learning, and other frontier techniques.
Continuously track scientific trends to maintain a state-of-the-art research practice.
Collaborate closely with Product and Engineering teams to translate domain challenges into algorithmic solutions with measurable product impact.
Represent the Research function at leadership forums, communicate priorities and outcomes, and align stakeholders around research strategies and milestones.

As part of this role you will, design, develop, and deliver high-quality, scalable, reliable, and extensible products. Work within our multidisciplinary R&D teams (Software Engineers, Linguists and NLP Research Engineers) and with the Product Management team.

This is an exceptionally exciting time to join a real AI company - when the very foundations of NLP are being redefined in front of our eyes. youll be at the forefront of that transformation, helping to shape the next generation of AI systems that are not only cutting-edge but also deeply impactful.

As a Research Engineer, you will design, develop, and implement algorithms and models that will enhance the products capabilities, performance, reliability, and scalability. Together with our algo and engineering team members, you will work closely with our product team members to implement algorithms that can be used to drive our business forward as well as the frontier of software development AI technologies.

Responsibilities:

Design, develop, implement and test algorithms and AI-empowered solutions for various product features and applications
Collaborate with cross-functional teams to understand business needs and translate them into algorithmic solutions
Perform research on emerging trends, algorithms, and cutting-edge technologies, and identify ways to incorporate them into our products pragmatically
Propose new and innovative solutions to complex problems and lead the development of algorithms in those areas
Design, cleanse, and utilize benchmarks throughout the process of the algorithm development

At our company, we see the world of cybersecurity differently. Instead of chasing threats, we believe the most practical approach is protecting data from the inside out. Weve built the industrys first fully autonomous Data Security Platform to help our customers dramatically reduce risk with minimal human effort.
At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities
Design and Build ML Infrastructure: Develop and maintain scalable, production-ready infrastructure for both traditional ML (anomaly detection, user behavior analytics) and LLMs across enterprise environments.
Optimize Model Performance: Analyze and optimize LLM and ML performance using techniques like knowledge distillation, quantization, and efficient data structures to boost efficiency and lower resource costs.
Deploy and Integrate: Collaborate heavily with software and data engineers to integrate models into production pipelines, cloud-native environments, and on-premises workflows.
Drive MLOps & Tooling: Manage the complete model lifecycle (monitoring, retraining, deployment) and actively build custom tools from scratch to improve the team's ML workflows.
Elevate Engineering Standards: Perform rigorous code reviews, ensure robust Python production standards, and provide technical guidance to data scientists and junior engineers.
Cross-Functional Partnership: Partner with cybersecurity researchers and product teams to translate research insights and threat analysis features into highly performant production code.
Open-Source Engagement: Actively engage with the open-source community by contributing code and expertise to relevant ML/LLM projects.

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
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.

Required ML-Engineering Lead
Our people are our greatest strength - and technology is our passion. Our team of innovators and subject matter experts, including veterans of elite military intelligence technology units, is transforming the way organizations protect themselves from drone threats.
As the global leader in cyber-takeover counter-drone technology, we design and deliver advanced, software-defined solutions that empower our customers to detect, take control, and safely land unauthorized drones - with precision and reliability.
Every day, we push the boundaries of innovation to meet real-world security challenges across industries and environments. Were proud of our cutting-edge technology, our global reach, and the impact we make in securing the skies.
Were seeking passionate professionals who thrive in a fast-paced, creative, and collaborative environment - those who want to be part of the next generation of airspace security innovation.
Join us and help make the world a safer place.
Work with the worlds leading cyber-takeover counter-drone technology provider and shape the future of safe airspace.
The Opportunity
We are starting a new ML/AI organization directly reporting to the CTO, to pioneer next-generation capabilities for our industry-leading defense systems. As a Founding ML-Engineering Lead, you will be the technical cornerstone of this initiative. This is a high-impact role designed for a practitioner who seeks total technical ownership of the machine learning lifecycle. You will be responsible for taking novel AI projects from initial concept through data collection, design, implementation, and evaluation, all the way to deployment.
The Technical Challenge Our ML initiatives span a diverse technical landscape. You will lead projects that range from field-oriented applications, where high accuracy and reliability are paramount, to research-oriented tools and agentic workflows designed to enhance our R&D capabilities and accelerate complex data analysis. Working in deep collaboration with our R&D teams, you will leverage unique, proprietary data to solve problems at the forefront of the counter-drone industry.
What You Will Do:
End-to-End Ownership: Lead the full technical execution of ML projects, ensuring every stage-from data acquisition to deployment-meets our rigorous standards.
R&D Collaboration: Partner closely with R&D departments to design data collection strategies and integrate ML-based tools and agents into their specialized workflows.
Versatile Implementation: Develop models and intelligent systems for a variety of use cases, ranging from real-time field performance to autonomous research-support tools.
Technical Authority: Act as a founding voice for ML implementation and strategy within the CTOs office.

We are looking for a Research Team Lead to establish and lead a cross-product research team focused on horizontal, high-impact initiatives that influence multiple offerings.
Unlike product-embedded research roles, this team drives foundational and strategic research projects across networking, security, identity, automation, and AI-driven capabilities. Examples include large-scale reasoning systems, autonomous policy frameworks, cross-domain detection and response concepts (xOps), and platform-wide intelligence capabilities.
You will combine deep technical expertise with strong leadership and execution skills -identifying impactful research directions, building a high-performing team, and turning advanced research into real platform capabilities used by thousands of customers worldwide.
Responsibilities
Technical Vision & Strategy:
Define and execute the roadmap for cross-product research initiatives.
Identify high-leverage research opportunities that impact multiple domains and products.
Drive long-term architectural thinking and influence platform evolution.
Balance innovation, experimentation, and production-readiness.
Team Leadership:
Recruit, mentor, and grow a multidisciplinary team of researchers (AI, data, algorithms, networking, security).
Establish high standards for research rigor, experimentation methodology, and engineering quality.
Foster a culture of ownership, collaboration, and technical excellence.
Research & Execution:
Lead complex, ambiguous research initiatives from ideation through validation and productionization.
Design large-scale experiments and validation methodologies using our data platform.
Drive innovation in areas such as:
Autonomous policy systems
Cross-domain detection and response frameworks
Large-scale reasoning and decision systems
Data-driven optimization and automation capabilities
Ensure research outcomes are measurable, scalable, and aligned with business impact.
Cross-Functional Collaboration:
Work closely with Product, Engineering, Architecture, and Product Research teams to translate research into shipped capabilities.
Provide technical guidance and influence cross-organizational decisions.
Act as a bridge between exploratory research and production systems.
Communication & Influence:
Present research findings and strategic recommendations to senior leadership.
Produce clear technical documentation, design proposals, and internal position papers.
Represent Platform Research as a center of excellence for cross-product innovation.