לוח משרות דרושים NLP/Machine Learning

ActiveFence 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 ActiveFence:
ActiveFence 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, ActiveFence 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, ActiveFence enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.

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 ActiveFence:
ActiveFence is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the worlds 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, ActiveFence 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, ActiveFence enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.
Hybrid:
Yes

We're looking for talented, versatile and highly independent Machine Learning Engineers to join our winning team. You will be in charge of end-to-end development and you'll have a massive impact on the product and the technical decisions made.
The ML Engineers are part of our infrastructure group, working closely with the exceptional research team, taking trained models and scaling them out to production.
Responsibilities
Take ownership of the entire machine learning engineering lifecycle - from building scalable training and evaluation pipelines to deploying models in production, with robust monitoring and maintenance systems.
Help in creating scalable solutions by enabling us to continuously increase the accuracy of our algorithms across thousands of clinics.
Designing a secured large-scale system that is suitable for sensitive patient data.
Continue to enhancing our deep learning infrastructure to supports our AI models at scale, including CI/CD, automation, testing and monitoring.
Collaborate with the research, medical and product teams in implementing ML solutions to the digital health space.

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.