לוח משרות דרושים NLP/Machine Learning משרה מלאה

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.

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.

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at our company.
Our team is part of our companys Personalization organization, a high-performing group that leverages our companys expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at our company scale and latency requirements. We are a team uniquely placed within our company, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future.
As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership.

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation.
AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops.
We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.

We are looking for a Backend Engineer to join our MLOps team and help build the infrastructure that powers cutting-edge AI models. In this role, youll manage the end-to-end MLOps lifecycle, designing event-driven systems that handle massive video data and moving compute-intensive, generative models from research to production. You'll collaborate closely with AI researchers and video-processing teams to ensure our AI services are scalable, reliable, and performant.

Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.
As a hands-on team lead, youll shape the technical roadmap for NLP and Speech, identifying key opportunities to invest in foundational technologies and grow the team through strategic hiring and mentorship. Youll work cross-functionally with product, engineering, and design partners to ensure that advanced research translates into robust, scalable features that define the future of AI-assisted content creation.

What We Are Looking For As a VP of AI Security Research you will lead, scale, and inspire multi-disciplinary teams focused on red teaming, sandboxing, adversarial testing, developing red-teaming engines, and guardrail protections for GenAI models and agentic AI systems. In this high-profile role, you will work closely with security research, product, engineering, and compliance teams to shape and deliver the next generation of AI cybersecurity solutions, while combining strategic vision with execution to effectively safeguard LLMs and agentic AI deployments at scale. Key Responsibilities
* Building and scaling global AI security teams, while providing mentorship to senior managers and fostering an innovation-driven security culture.
* Overseeing advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems, and delivering executive-level threat intelligence and risk assessments to inform corporate AI strategy.
* Defining and implementing AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF, and operationalizing automated red-team engines to continuously stress-test models at scale.
* Partnering with product and engineering to design and deploy enterprise-ready AI guardrails, including policy enforcement layers, monitoring pipelines, and anomaly detection systems – and championing secure deployment practices for GenAI (including agent orchestration via MCP and A2A workflows).

About Alice:
Alice is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the world’s largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, Alice empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, Alice enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.

Hybrid:
Yes

Alice partners with the world’s leading AI labs to deliver best-in-class model assurance, red teaming, evaluations, and post-training data programs. We’re looking for a Technical Engagement Lead to guide the technical success of these strategic customers. In this role, you’ll be the key technical counterpart to frontier-model teams—helping them design, structure, and execute complex AI safety programs. You won’t be building prompts or running evals yourself; instead, you’ll lead the technical architecture and orchestration of our work, ensuring quality, coherence, and impact across multiple workstreams. You’ll work hand-in-hand with a Senior Account Manager, delivery teams, researchers, and product leaders to help GenAI customers push forward safely and responsibly. What You’ll Do
* Serve as the primary technical partner for leading LLM labs and GenAI-native organizations
* Translate customer goals into structured evaluation, red teaming and data programs
* Design engagement architectures across multiple parallel contracts and initiatives
* Ensure technical excellence and consistency in all deliverables
* Lead technical discussions with research, safety, and product teams
* Identify risks, dependencies, and evolving needs early, and drive resolution
* Stay ahead of emerging evaluation methodologies, safety approaches, and model risk trends
* Partner internally with Delivery, Research, Product, and Account Manager to ensure seamless execution
Why Alice Work with the world’s leading AI labs
* Help shape the safety and trustworthiness of next-generation AI models
* Join a mission driven, high performing team
* Enjoy opportunities for growth and professional development in a cutting-edge field.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.




Hybrid:
Yes

Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting?edge AI and world?class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever?changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities
* Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
* Develop, deploy and integrate AI solutions and agentic frameworks, creating both command?line tools and interactive notebooks that support our team’s research and workflow automation needs.
* Build and manage data pipelines and databases (SQL) for large?scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
* Integrate research into production by implementing the latest generative AI advancements (including white?box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
* Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end?to?end processes for prompt generation, labeling, and response evaluation.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.