לוח משרות דרושים NLP/Machine Learning

Required Senior NLP Researcher
Tel Aviv Full-time
About The Position
We redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. This is where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
Our AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
Our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Dream-Maker Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

Realize your potential by joining the leading performance-driven advertising company!
As a Team Leader on the advertiser side ML group in our TLV Office, youll play a vital role in shaping how user intent is modeled at scale and how rich behavioral data is transformed into smarter recommendations. You will lead the design and evolution of large-scale Deep Learning models that directly improve advertiser performance and marketplace efficiency. By guiding team members and driving technical direction, youll turn modeling gaps into scalable production solutions. Your work will influence how millions of users discover content and how advertisers achieve measurable impact.
How youll make an impact:
Lead the design and evolution of our companys models
Own end-to-end ML delivery in production
Lead and develop ML engineers
Translate marketplace objectives into modeling strategy
Play a part of our companys tech organizations growth in the agentic development era.

Realize your potential by joining the leading performance-driven advertising company!
As a Senior Machine Learning Engineer, youll play a vital role in turning algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
How youll make an impact:
As a Senior Machine Learning Engineer, youll bring value by:
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more.

Realize your potential by joining the leading performance-driven advertising company!
As a Senior MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Realize your potential by joining the leading performance-driven advertising company!
As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Required ML Engineering Team Lead
Why us:
Youll work in an awesome environment alongside some of the most innovative people in the industry, using cutting-edge technologies and tools (video editing, Gen AI, data, etc.). You have the opportunity to directly influence the products and tools used by our clients, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN - and thats just the beginning of what we have to offer! Join us and be a part of the best team in tech as we Fuel the Fandom worldwide.
As a ML Engineering Team Lead, you will lead a multidisciplinary team of algorithm and software engineers responsible for designing, building, and operating the next-generation content creation engine. The team focuses on leveraging agentic systems and advanced ML technologies to orchestrate complex, end-to-end production workflows at scale.
In this role, you will translate high-level product and business goals into robust, production-ready solutions, working hands-on across the full lifecycle - from research and system design to deployment, monitoring, and continuous improvement. You will collaborate closely with Product, Platform, Data, and other R&D teams in a fast-paced, agile environment, ensuring that algorithms and software are seamlessly integrated into real-world, high-throughput systems.
You will combine technical leadership, architectural thinking, and people leadership to drive innovation, execution, and delivery, while shaping how intelligent, automated content is created and scaled across our products.
What youll do:
Lead and mentor a multidisciplinary team of algorithm and software engineers, fostering ownership, technical excellence, and professional growth.
Own the delivery of complex, end-to-end systems for automated content creation, from early design and experimentation through production deployment, monitoring, and iteration.
Drive the design and orchestration of agentic systems, working hands-on with the team to integrate ML models, business logic, and software infrastructure across research, engineering, and production at scale.
Translate product and business challenges into technical solutions, defining system architecture, prioritizing initiatives, and guiding execution in an agile environment.
Ensure production readiness and reliability, overseeing deployment, monitoring, performance, and continuous improvement of algorithms and services in a live environment.
Collaborate closely with Product, Platform, Data, and other R&D teams, aligning technical execution with product strategy and business goals in a multidisciplinary setting.
Continuously evolve technically and professionally, encouraging knowledge sharing, joint problem-solving, and awareness of emerging trends in ML, agentic systems, and large-scale software architectures.

We are looking for a motivated and experienced Machine Learning Platform Engineer to join our dynamic team.

In this role, you will collaborate closely with data scientists and DevOps professionals to design and build the infrastructure, ecosystem libraries, and pipelines that power our data science initiatives. You will take ownership of model development, monitoring, and maintenance, working hand-in-hand with data scientists on a daily basis.

If youre passionate about AI, machine learning, and writing high-quality code-and are eager to contribute to innovative, impactful do good projects in the digital health space-wed love to hear from you!

What you'll be doing:
Design, develop, and maintain our machine learning ecosystem libraries.
Build and manage data science code, Docker images, and Kubeflow Pipelines (KFP).
Create and maintain CI scripts to ensure seamless integration and delivery.
Conduct thorough code reviews to uphold high-quality standards.
Collaborate closely with data scientists, understanding and addressing their evolving needs.
Work alongside software developers to seamlessly integrate machine learning models into production systems.
Stay current with the latest advancements in machine learning, leveraging innovative techniques to enhance the companys products and services.

Design and execute research projects using advanced methodologies and tools to generate actionable insights that improve decision-making.
Analyze data and apply critical thinking to identify innovation opportunities and optimize research processes.
Prepare scientific reports and presentations to effectively communicate findings and recommendations to stakeholders.
Collaborate across teams and consult with experts, demonstrating adaptability, receptiveness to feedback.

We are looking for an experienced Deep Learning & AI Infrastructure Engineer to join our AI team. In this role, you will develop and deploy advanced deep learning models for signal processing and build the infrastructure and tooling required to scale AI training and inference in both research and production environments.
You will be responsible for the end-to-end lifecycle of AI workloads, including data ingestion and preprocessing pipelines, model training infrastructure, efficient inference systems, and automated experiment tracking.
Key Responsibilities
Design, implement, and optimize deep learning models and pipelines for signal and image analysis.
Build and maintain AI infrastructure components to support model training, versioning, monitoring, and deployment.
Develop scalable data processing pipelines for datasets, including ingestion, labeling, augmentation, and preprocessing at scale.
Implement automated training workflows using tools such as ClearML or other experiment tracking platforms, ensuring reproducibility and model governance.
Collaborate with system engineers to integrate AI models into real-time radar systems and ensure efficient inference performance.
Optimize distributed training and resource utilization.
Run performance tuning, testing, and benchmarking for both training and inference workloads.
Document infrastructure components, training procedures, and model lifecycle processes.

we are looking for highly skilled Ph.D. level researchers for an Algorithmic Trading Research Group in Tel Aviv. our company office is located at the TLV expo center, right next to TLV University train station and offers highly competitive compensation packages.
Our formula for success is to hire exceptional people, encourage their ideas and reward their results with competitive compensation packages.
Researchers at our comoany apply tools from a variety of disciplines including statistics, control theory, machine learning, optimization, and signal processing to develop algorithmic trading strategies. Our research team collaborates on idea generation and strategy development, while encouraging independent exploration and original approaches. Researchers have access to clean data integrated with a high performance computing grid and the support of dedicated software developers.
Job Description
Develop algorithmic trading strategies and improve existing strategies
Identify inefficiencies in the financial markets and characterize them with mathematical models
Predict price movements using statistics, signal processing and machine learning
Apply optimization techniques to construct optimal portfolios
Design automated trading agents that achieve efficient execution
Direct software developers in the translation of the research into production software.

we are looking for highly skilled Machine Learning Engineer for an Algorithmic Trading Research Group in Tel Aviv. our company office is located at the TLV expo center, right next to TLV University train station and offers highly competitive compensation packages.
As a Machine Learning Engineer, you will be an integral member of an algorithmic trading team comprised of experienced technologists and quantitative researchers. Your team will work closely to solve challenging technical problems and contribute to our full tech stack, from hardware and software development to grid computing. You will be surrounded by cutting edge technology, offered training and continuing education opportunities, and given immediate responsibility. We are looking for creative technologists, natural programmers, and disciplined engineers eager to develop new technologies that directly impact our business.
How you will make an impact:
Build infrastructure for running Machine Learning algorithms on big data.
Optimize Machine Learning algorithms to run under latency constraints.
Parallelize Machine Learning algorithms to run on a parallel compute grid.
Build software for data acquisition and cleaning that can handle hundreds of terabytes of data.
Build data visualization tools for feature exploration and model verification.
Integrate Machine Leaning algorithms into trading strategies simulations to verify end to end performance improvements.
Contribute to technological innovation through exploration of cutting-edge hardware, software, and methods.
As an active member of the research team you will have an impact on the technological direction and the analysis of trade-offs between complexity and performance.

We are hiring Senior and Staff ML Engineers that sit within Safety Systems / autonomy organisations, building critical behaviours for Level 2 to level 4 driving. It is highly product-focused: you will train and iterate on end-to-end driving models and get them shipped into the car on a fast timeline measured in months. The opportunity is to own the full loop from data and training through evaluation and on-road validation, with direct impact on high-priority commercial deliveries (including the Nissan MVP). You will join a small, high-ownership teams at the point of rapid growth, where execution and real-world outcomes matter.
Key responsibilities
Develop the AI driver model architecture and training algorithms to introduce and enhance the safety behaviors for L2/L3/L4
Own key parts of the training model lifecycle, including evaluation strategy, success metrics, and iteration planning.
Mine, bucket, and curate real-world and synthetic data to teach specific driving behaviours, and implement data schemes to support training.
Run and analyse on-road and offline experiments, translate results into clear next steps, and drive improvements through repeated training cycles.

We are looking for an ML Engineer / MLOps Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.
You will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle management-the foundation of our product.
Responsibilities:
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.
End-to-end ML delivery - enabling model performance development, training, validation, testing, and version control.
Build and support monitoring and observability tools - dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as: Feature Store, Vector / Graph Databases.
Data wrangling - supporting and enabling data requirements for research, training, validation, and testing.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.

Were looking for a Senior Data Scientist to take full ownership of high-impact ML problems within our DSP platform.
You will work on core bidding, budget optimization, and prediction systems that operate at massive scale and strict latency constraints. This role combines deep modeling expertise, experimentation rigor, and strong product intuition.
You will be expected not only to build models - but to define problems, challenge assumptions, and drive measurable business impact.
What Youll Do:
Own end-to-end ML projects: problem definition → research → modeling → offline validation → production deployment → online A/B testing → impact analysis.
Develop and improve models for: Bid optimization , Conversion rate / pLTV prediction, Budget pacing and allocation, Auction dynamics & win-rate modeling.
Analyze large-scale, high-dimensional auction and user-level datasets to extract actionable insights.
Design robust feature engineering pipelines across behavioral, contextual, and advertiser-level signals.
Improve model performance under real-time constraints (low latency, high throughput).
Lead experimentation design and statistical validation of online tests.
Collaborate closely with engineering and product to translate research into scalable production systems.

We are looking for a hands-on AI Engineer to help build our core intelligence engine and infrastructure. In this role, you will work on exploring and building autonomous solutions that execute security workflows end-to-end, moving capabilities from research concepts to scalable production features.
What You Will Build:
● Internal AI Infrastructure: Contribute to a shared internal AI platform for models, data, training, and observability.
● Autonomous Capabilities: Build solutions that automate complex security operations and investigative workflows.
● Active Defense Mechanisms: Help productize runtime guardrails into customer-facing protective controls and monitoring systems.
Responsiblities:
● Develop and implement the engineering backend for AI-driven security features.
● Build and maintain the internal mechanisms that allow for safe and scalable AI feature deployment.
● Collaborate with AI Researchers to translate findings into production-grade autonomous workflows.
● Implement runtime guardrails and AI-focused data security capabilities.