לוח משרות דרושים NLP/Machine Learning

we are looking for an AI Engineer to lead our MLOps team and take full ownership of our machine learning infrastructure used to train, evaluate, and deploy our state-of-the-art computer vision models. In this role, you will work closely with other team leads and Product to plan and build the future of core AI platform. You will help define technical direction, make long-term architectural decisions, and translate company goals into executable plans, directly impacting ability to scale its AI capabilities and the overall success of the company.
Responsibilities

Manage and lead the MLOps team, including mentoring, professional development, and day-to-day technical guidance
Plan and own quarterly roadmaps, sprint planning, task breakdown, and execution, ensuring alignment with company and product priorities
Design, build, maintain, and evolve ML infrastructure for training, evaluation, and deployment of computer vision models
Own the end-to-end ML lifecycle in production, including experimentation workflows, training orchestration, model versioning, deployment, and monitoring
Balance delivery and technical excellence by making architectural decisions and enforcing engineering best practices
Work closely with research, data, product, and platform teams to move models reliably from research to production
Actively contribute code to critical components and review design and implementation across the team
Evaluate and introduce new technologies and tooling to improve scalability, reliability, and developer productivity

we are a game-changing startup that's giving advanced electronics the power to report on their own health. In a digital world built for autonomous driving, cloud computing, and AI, we depend on computing systems daily. But how can we guarantee their safety, reliability and functionality? we are the first-ever company to provide visibility into next-gen chips while they are operating, based on the power of on-chip monitoring, machine learning, and data analytics.
Here at our company, you'll be part of a team that's unlocking deep insights to make electronics more reliable, efficient, and high-quality. We're trusted by industry leaders in data centers, automotive, communications, and consumer devices - we work with the world's largest and most notable companies in tech.
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 company 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 a game-changing startup that's giving advanced electronics the power to report on their own health. In a digital world built for autonomous driving, cloud computing, and AI, we depend on computing systems daily. But how can we guarantee their safety, reliability and functionality? we are the first-ever company to provide visibility into next-gen chips while they are operating, based on the power of on-chip monitoring, machine learning, and data analytics.
Here at our company, you'll be part of a team that's unlocking deep insights to make electronics more reliable, efficient, and high-quality. We're trusted by industry leaders in data centers, automotive, communications, and consumer devices - we work with the world's largest and most notable companies in tech.
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 company 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 currently looking for a Senior Machine Learning Engineer to design and implement scalable and integrate machine learning solutions into production. You will work with modern technologies like Node.js, Python, Kafka, MongoDB, and OpenSearch, AirFlow, while driving architectural decisions and CI/CD best practices. This role combines backend engineering excellence with ML deployment expertise.

The Senior Machine Learning Engineer will report directly to the Director of R&D.

Your key responsibilities will include:

Architect and develop MLE services using Python, ensuring high performance, reliability, and scalability.
Collaborate with Data Science teams to productionize ML models (model serving, monitoring, retraining pipelines).
Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring.
Design and implement system architecture for distributed, event-driven systems.
Integrate and optimize Kafka for real-time data streaming and event processing.
Design and manage MongoDB schemas and queries for optimal performance.
Implement and maintain OpenSearch clusters for search and analytics use cases.
Ensure security, observability, and fault tolerance across all services.
Mentor team members and contribute to engineering best practices.

As a Data Scientist, you will sit at the very core of our company. This isn't just a role about maintaining models-its about transformation. You will be the architect of a "learning machine," turning raw data into usable metrics and developing the statistical algorithms that power our business performance.

You will collaborate with Data Engineers and Product Managers to translate the "voice of the customer" into digital insights that define the industry standard.

Key Responsibilities:
Drive Actionable Insights: Analyze diverse data sources to create insights that directly fuel business growth.
Optimize Performance: Build advanced ML algorithms for bidding-utilizing classification and clustering to maximize campaign performance.
Innovate with GenAI: Leverage Generative AI techniques to query data for intelligent insights and automate decision-making.
Own the Lifecycle: Lead projects from initial exploration and Proof of Concept (POC) to scalable production environments.
Scalability & Performance: Ensure our data pipelines and ML models can handle large-scale, dynamic datasets with high efficiency.
Metric Ownership: Create and own key performance metrics that drive innovative product solutions.

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a ML & Big Data Analyst look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of data and algorithms.
Utilize your deep understanding of data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.

Were looking for a visionary, technically grounded, hands-on practitioner to help us explore, shape, and represent the future of AI agent trust. You will develop a deep understanding of how autonomous and agentic systems are built and used in the real world, and help internal teams and the broader ecosystem reason about how agents can be trusted, governed, and safely deployed.

You will report to the CPO, work closely with the CTO, and partner across product, engineering, research and data teams. This role sits at the intersection of emerging agent technologies, product strategy, hands-on technical exploration, and external thought leadership.

What Youll Do:

Research & Ecosystem Insight

Stay current on agentic systems and autonomous architectures, with a focus on how agentic interactions are enabled across the open web.
Analyze how AI agents are designed, deployed, and integrated across industries and use cases.
Track trends, standards, and shifts in agent architectures, behaviors, and interaction patterns.
Develop models and approaches to profile, classify, and assess agentic interactions.
Technical Exploration & Prototyping

Build lightweight prototypes or proofs-of-concept to validate ideas and assumptions.
Evaluate third-party frameworks, tools, and integration approaches.
Translate emerging concepts into clear technical direction, architectures, or requirements.
Product Enablement

Advise product teams as they explore and productize agent-trust solutions.
Help reason about agent behavior, system boundaries, reliability, and safe operation.
Act as a bridge between research, product, engineering, and data.
Thought Leadership

Represent the company on topics related to AI agents, autonomy, and trust.
Contribute to blogs, whitepapers, talks, or industry discussions that shape how the market thinks about agentic systems.
Engage with partners, customers, and the broader ecosystem to share insights and learn from real-world feedback.
Help position the company as a credible, forward-looking voice in AI-agent trust.
Communication & Collaboration

Communicate complex ideas clearly through documentation, presentations, and discussions.
Build shared language and understanding around agentic systems across the organization.
Collaborate effectively in a fast-moving, cross-functional environment.

Our data science team is seeking a highly skilled AI researcher with expertise in modern AI methods (e.g., multi-agent architectures, reinforcement learning on LLMs) and a passion for transforming theoretical challenges into real-world products.
In this role, you will leverage our unique clinical datasets to design and build groundbreaking solutions that provide medical benefits to millions of people. You will take full end-to-end ownership of your models - from ideation and research to production deployment and ongoing monitoring.
Working across both research and production environments, you should have proven experience in developing and deploying machine learning algorithms, along with strong interpersonal and collaboration skills. We value independent thinkers who are also proactive doers.

What Youll Be Doing:
Develop clinical AI models to support Ks clinic workflows, with a focus on patient-facing applications
Design and implement scalable, efficient pipelines for data preprocessing, information extraction, and model training
Stay up to date with the latest AI research and best practices, and translate them into production-ready solutions
Communicate complex technical concepts and solutions to non-technical stakeholders
Collaborate with MLE and AI engineering teams to deploy scalable, robust solutions

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.

We are looking for an experienced ML/AI engineer to anchor our ML Platform team. You will lead the effort to productize our Large Language Models, transforming experimental code into robust, efficient services. Your goal is to build the infrastructure that allows our Data Scientists to move fast without breaking production.

What you'll be doing:
Model Development & Optimization

Fine-tuning & Engineering: Develop and fine-tune LLMs/classic models for specific medical tasks (condition detection, dialogue systems) using internal datasets.
Research to Production: Partner with Data Scientists to develop experimental code into scalable, production-ready modules.
Platform Engineering & Infrastructure

Pipeline Orchestration: Build and maintain complex ML workflows using Kubeflow Pipelines (KFP) or similar orchestration tools.
Internal Tooling: Develop and manage the internal Python ecosystem-libraries, SDKs, and utilities-that the Data Science team uses for daily development.
CI/CD & Automation: Write and maintain CI/CD scripts to automate the testing, versioning, and deployment of machine learning artifacts.
Production Standards & Integration

System Integration: Work with backend developers to integrate trained models/agents into the core application architecture.
Code Quality: Enforce high engineering standards through code reviews, ensuring that research code meets production reliability and maintainability requirements.
Requirements Engineering: Translate evolving data science requirements into concrete infrastructure and platform features.

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 seeking a hands-on AI Team Lead to guide a small, high-performing, cross-border team focused on applied computer vision and deep learning. This role combines strong technical leadership with business awareness, requiring a balance between innovation and reliable delivery.
The AI Team Lead will take ownership of model development from concept to production, ensuring that every solution delivers clear product value and aligns with commercial objectives. You will work closely with product, engineering, and business stakeholders to translate real-world farming challenges into scalable AI solutions.
What Youll do:
Lead a team of two-three AI engineers and a data analyst.
Stay hands-on with modeling, architecture, and experimentation (PyTorch, TensorFlow, OpenCV, etc.).
Prioritize projects and research directions based on business value, not academic curiosity.
Translate business needs into clear technical milestones, balancing accuracy vs. speed, performance vs. ROI.
Define and enforce quality standards in modeling, validation, and deployment.
Mentor and grow a strong, self-driven technical team through feedback, reviews, and clear objectives.
Collaborate daily with business, backend, and QA teams to align expectations and adjust priorities quickly.

Were seeking a Team Lead - Generative AI Engineer to lead a team of engineers in designing, developing, and deploying production-grade AI systems. This role is ideal for someone who is both a strong technical contributor and an experienced people leader-capable of driving architecture decisions, mentoring team members, and delivering innovative AI solutions at scale.
You will be responsible for guiding the end-to-end lifecycle of Generative AI applications, ensuring technical excellence, scalability, and alignment with business needs. This includes working across backend systems, RAG pipelines, prompt engineering, and cloud-native deployments.
Key Responsibilities
Leadership & Team Management Lead and mentor a team of AI/ML engineers, fostering growth and technical excellence.
Define and enforce coding standards, architectural patterns, and best practices.
Collaborate with stakeholders to translate business needs into AI-driven solutions.
Manage project timelines, technical risks, and team deliverables.
Generative AI & Prompt Engineering Integrate and optimize applications using LLM provider APIs (OpenAI, Anthropic, etc.).
Design prompts with advanced techniques (few-shot, chain-of-thought, chaining, context crafting).
Implement safeguards (guardrails, structured output validation, injection protection).
Architecture & Backend Development Build scalable backend services in .NET (C#) and Python, working with SQL and APIs.
Develop and manage RAG pipelines, conversational AI systems, and summarization tools.
Drive observability: tracing, logging, monitoring for LLM-powered systems.
Evaluation & Optimization Benchmark and evaluate LLMs using custom datasets and automated testing.
Oversee system reliability, performance tuning, caching, and optimization.
Ensure solutions meet enterprise-grade standards for security and scalability.

Imagine what you could build with Large Language Models and NLP.
The Algo ML team develops and integrates AI systems, including Large Language Models, Retrieval Augmented Generation systems, and intelligent agents, into our technologies and workflows.
We are looking for an outstanding student to help build state of the art NLP algorithms and AI applications for the Hardware Technologies group, from concept to launch. Youll partner closely with engineering stakeholders to shape the roadmap, deliver high quality solutions, and continuously improve them based on usage and feedback.
If you are excited about the intersection of LLMs, applied NLP, and intelligent systems, this role will both inspire and challenge you.


In this role, you will join a team of researchers and engineers developing AI systems and domain-specific Large Language Models for cutting-edge our products.
You will contribute across the research-to-product pipeline, from algorithmic exploration to prototype development and evaluation, and gain hands-on experience in building intelligent systems at scale.

Responsibilities:
Research and develop algorithms in the areas of NLP and Large Language Models.
Assist in building and evaluating AI systems such as RAG pipelines and intelligent agents.
Support the development of prototypes and demos for early feedback and iteration.
Collaborate with researchers and engineers across multiple teams and sites.
Develop tools and processes to analyze and evaluate model performance.
You will gain exposure to the full lifecycle of intelligent AI experiences, from early research ideas, through experimentation and validation, to product-ready systems used worldwide.

We are seeking an experienced ASIC AI/ML Engineer with deep expertise in AI/ML infrastructure and application development specifically for semiconductor design verification disciplines. The ideal candidate will have a proven track record of delivering end-to-end AI solutions from concept to large-scale production deployment.
In this role, you will collaborate directly with architects, designers, verification engineers, software teams, and backend specialists to define best practices and deploy production-ready AI-driven workflows and applications. Your focus will be on implementing LLM, GenAI, and classical ML solutions that transform our ASIC design verification processes and accelerate our path to tape-out.
Key job responsibilities
Develop and maintain scalable AI/ML infrastructure for ASIC design and verification teams
Architect, develop, and deploy production-ready AI/ML applications for semiconductor design workflows
Design and implement GenAI solutions including LLMs and agentic AI systems for verification processes Invent innovative AI-driven solutions to eliminate identified inefficiencies in design and verification flows
Establish best practices and standards for AI/ML application development in semiconductor environments
Create monitoring and observability frameworks for AI model performance in production design environments
Collaborate cross-functionally with architects, designers, verification engineers, and software teams
Research and evaluate emerging AI technologies for applicability to semiconductor design challenges.