לוח משרות דרושים NLP/Machine Learning

Our mission is harnessing humanitys collective intelligence to solve the most impactful problems. After building a first-of-its-kind technology capable of automatically combining algorithms and structured datasets, and enabling deep discoveries, were now incorporating large language models to make our insights easier to understand, to close the impact loop, and open up advanced analytics to a broader audience.
Job Description
What will you do?
Build a strategic technological component in a game-changing product.
Play a key part in establishing a unique, multidisciplinary pioneering team.
Bring your analytical skills and curiosity to life through performing applied research in NLP.
Develop NLP based solutions from ideation to full production code, building software that implements AI algorithms while being robust, scalable and delivering high performance.
Work with various interfaces Product, Full Stack Developers, Researchers, Data Scientists, UX and many more.
Unleash your creativity and passion for technology to create state of the art, one of a kind products.
Develop and implement state-of-the-art natural language processing pipelines.

This is a research‑first role focused on deeply understanding LLM internals to improve the security of AI agents. Youll design careful experiments on activations and interpretable features- e.g., probing, attribution & ablation/patching, representation‑geometry analyses-to uncover mechanisms behind jailbreak, indirect prompt injection, and other attacks. Then translate those insights into signals that can be used for detection and analysis of a model response.

The field of LLM interpretability at scale is exploding, with several major publications in the last months, and major opportunities for innovation.



What Youll Do

Investigate model internals, including activation/features analysis, unsupervised clustering, discovery of directions in latent space, etc. It may also require training specific model parts to improve interpretability metrics.
Design security‑grounded evaluations: curate datasets for different attack types, evaluate performance of different white box (model internals) methods compared to black box (input/output only) baselines.
Publish and share: produce Zenity Labs posts and open artifacts; when the work is strong, aim for tier‑1 ML venues (NeurIPS, ICML, etc.) and security forums. A publication of code and/or trained models in cases of community relevant novelty.
Build tools: Several open source libraries exist (like Anthropics attribution graphs infra), but the research in the field is very dynamic, which will require you to build and adapt tools to your own research directions. This also includes agents to automate research work and distill knowledge from designed experiments.

As a Senior MLOps Engineer , you will design, build and scale our machine learning infrastructure. You will lead the end to end model lifecycle, from data and training to deployment and monitoring, ensuring reliable and high performance ML systems in production. You will work closely with our research and engineering teams to bring advanced AI models into production and help shape the future of our AI capabilities.

We're looking for a skilled and motivated Data Science Team Lead to guide a team of talented data scientists in developing real-time, machine learning-based products. Youll play a key role in driving innovation - researching, designing, and deploying advanced ML models that directly enhance user experience and product performance.

This is an exciting opportunity for a hands-on leader who thrives in a fast-paced, impact-driven environment.

Responsibilities:

Lead, mentor, and inspire a team of data scientistsfostering a culture of collaboration, innovation, and technical excellence
Guide team members personal and professional development
Collaborate with product and engineering teams to identify challenges, uncover opportunities, and drive data-driven solutions
Recruit and retain top-tier talent as the team grows
Research and develop ML models using cutting-edge techniques across a range of domains
Generate new ideas and insights to improve performance and deliver business value

We are looking for a Machine Learning 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.

As a Tech Lead on the ML team , 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 managementthe foundation of our product.

Responsibilities:

Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as:
Feature Store centralizing feature engineering and serving across teams.
Vector Databases enabling large-scale embedding storage and retrieval for advanced ML applications.
GPU Cluster Scaling optimizing distributed training and inference infrastructure.
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.

We are looking for a senior deep learning algorithm developer to join our growing team under our companys Algorithms Group. The team is building an innovative multimodal learning framework aimed at improving autonomous driving performance by understanding long-tail cases and providing actionable navigation insights. Were combining state-of-the-art vision-language models to revolutionize how we train, validate, and scale our autonomous systems. If youre passionate about deep learning and engineering high-impact autonomous solutions - this is the place for you.
What will your job look like:
Own dataset curation activities- acquiring, cleaning, labeling, and tailoring multimodal data to meet model training and validation requirements.
Train and fine-tune LLMs, VLMs, and VLA models to interpret visual scenes and produce actionable navigation insights supporting autonomous vehicle decision-making.
Lead robust validation of advanced multimodal models - ensuring reliable vision-language-action alignment and consistent performance across diverse real-world driving scenarios.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
Youll have the opportunity to influence the strategic direction of language-driven autonomy - proposing new ideas, shaping model capabilities, and driving innovation from research to real-world deployment.

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.

Are you a passionate Applied Scientist ready to make a global impact? Join our elite AI and data science team.
If you are a talented Applied Scientist with strong technical skills, a passion for turning data and research into real-world impact, and the ambition to design, experiment, and ship innovative ML and AI solutions, we would love to talk to you!
In our team, you will:
Develop ML models to detect and disrupt cyberattacks.
Collaborate with security experts to incorporate domain knowledge into ML solutions.
Work with truly large-scale data to create and refine high-quality training datasets.
Deploy ML models into production, monitor their performance, and continuously improve them.
Stay up to date with the latest advancements in ML/AI and apply them to complex cybersecurity challenges.

We are looking for a AI Automation Engineer to join our team.

We're searching for a talented and passionate technologist to implement AI driven innovation by integrating AI Agents and AI APIs in automation processes and Internal Tools. As a key member of the team, you'll play a vital role in developing and implementing innovative solutions to enhance our company's efficiency, productivity and quality. You'll leverage your expertise in artificial intelligence (AI) , automation tools, and software development to design, build, and deploy tools that streamline workflows, automate repetitive tasks, provide insightful data analysis, reduce costs and help the company scale.

Responsibilities
Work with the AI Projects Manager to research, design, and develop AI-powered solutions (e.g., chatbots, machine learning models) to automate tasks, unlock scaling opportunities and generate efficiencies across the company.
Build internal tools that automate workflows, improve data accessibility, and improve data accessibility, and facilitate collaboration within the company.
Integrate AI and internal tools seamlessly with existing systems and infrastructure to ensure smooth operation and data flow.
Write clean, maintainable, and well-documented code or automation processes, adhering to best practices and security standards.
Conduct unit tests and implement test-driven development (TDD) methodologies to ensure code quality and reliability.
Monitor and maintain deployed tools, identifying and resolving technical issues promptly.
Stay up-to-date with the latest advancements in AI, automation tools, AI APIs, and internal tool development best practices.

As an AI Engineer, youll build full-stack features that deliver seamless user experiences combining robust engineering with advanced AI capabilities.

Responsibilities
Design and deploy agent-based systems for real-world use cases
Build end-to-end features: backend APIs, data models, and React-based UI
Integrate AI and agentic logic into the core product
Develop backend pipelines for autonomous agents and workflow automation
Optimize model accuracy, reliability, and performance
Work closely with product, data, and UX teams to align AI with business and user needs

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.

We are looking for a senior ML engineer to join us and built groundbreaking systems designed to handle massive-scale data at an unparalleled magnitude.
In our team we engineer mission-critical solutions that address some of the complex and high-stakes challenges at a national level.
Our unique data poses novel challenges, pushing us to continually innovate and redefine what's possible.
As a Senior ML Engineer you will:
Engineer, design and implement robust, high-performance data-drive pipelines and infrastructure.
Design critical systems for production environments, including observability, monitoring, CI\CD pipeline and resource management.

Required Sr. ML Engineer- Platform
The Job
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world ML services and customer deployments. In this role, you'll own reliability, velocity, and cost efficiency for our products and customer deployments.
Responsibilities
Design, develop, build and maintain the best solutions for our production platform.
Everything as a code approach (IaC): Run our infrastructure with a wide range of technologies including Ansible, Terraform, and Kubernetes
Work closely with our data scientists and developers to create training, inference and serving pipelines.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production, and test environments.

Required Senior NLP Researcher
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.

Required MLOps Engineer - AI Infra Group
Tel Aviv Full-time
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world production-grade AI infrastructure. This group builds scalable, high-performance AI systems for internal users and external customers, designed to run seamlessly across cloud and on-premise environments using the latest hardware advancements.
Responsibilities
Design, build, and maintain scalable Kubernetes-based infrastructure for ML workloads across on-premise and cloud environments
Architect hybrid infrastructure solutions enabling seamless model flow from on-premise training environments to cloud-based inference deployments
Implement model registry and artifact management strategies that support cross-environment synchronization, versioning, and governance
Design secure, efficient data and model transfer mechanisms between on-premise and cloud (networking, storage replication, caching strategies)
Implement and manage GPU scheduling, resource allocation, and cluster autoscaling for heterogeneous compute environments
Build and maintain CI/CD pipelines for ML systems, including model versioning, testing, and promotion across environments
Develop observability solutions (logging, monitoring, alerting) for ML infrastructure across hybrid deployments
Collaborate with ML Engineers to define infrastructure requirements and SLAs for training and serving workloads.