SUMMARY

We're looking for a AI Research Scientist to join us in spreading the power of Wiz and push the boundaries of AI in cybersecurity. You'll be at the forefront of developing novel AI models - focusing transformers and LLMs - that advance how cybersecurity operates. Contribute to the wider AI and cyber communities through publications and conference presentations, establishing Wiz as a thought leader at the intersection of AI and cybersecurity.

WHAT YOU’LL DO

• Develop and research novel AI models, focusing on transformers and deep learning. Lead mid- to long-term projects aimed at advancing AI-driven features in the cybersecurity domain for Wiz products.
• Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
• Stay informed about cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions’ accuracy, efficiency, and scalability.
• Collaborate with engineering teams to design, build, and maintain production pipelines. Work closely with the Security Research and Product teams to define research goals.
• Publish research findings and AI thought leadership content and present at leading conferences such as NeurIPS, ICML, or CVPR.

WHAT YOU’LL BRING

• An M.Sc. degree in computer science, statistics, or a related field is a must; a Ph.D. degree is an advantage.
• At least 3 peer-reviewed publications in reputable academic journals or conferences.
• 5+ years of experience in leading and managing data science and machine learning projects, preferably at the intersection of AI and cybersecurity.
• Experience and hands-on familiarity with distributed cloud systems.  
• Strong knowledge of deep learning models and common model architectures such as transformer models, LLMs, CNNs, RNNs. Knowledge of programming languages that are used in AI research—like Python—and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch).
• Proven ability to work independently in a fast-paced environment and come up with creative solutions to challenging problems.
• Excellent communication (both written and verbal) and presentation skills.

ADVANTAGE

• Knowledge of cybersecurity principles, attack vectors, and defense mechanisms.
• Experience speaking at data science and AI conferences like NeurIPS, ICML, or CVPR.

SUMMARY

We’re looking for a Data scientist Expert to join us and spread the power of Wiz. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at Wiz. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the company’s security posture.

WHAT YOU’LL DO

• Lead applied research on AI agents and LLM-driven features in the Wiz platform - from autonomous threat investigation agents to AI-powered security operations workflows
• Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
• Collaborate with engineering teams to design, build, and maintain production pipelines
• Work closely with the Security Research and Product teams to define research goals
• Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
• Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability

WHAT YOU’LL BRING

• An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience
• 5+ years of experience in leading data science and machine learning projects, with significant hands-on work building LLM-based applications or AI agents
• Deep practical experience with LLMs - prompt engineering, fine-tuning, model selection, and understanding trade-offs across providers and model families
• Experience with distributed cloud systems - hands-on familiarity with cloud-native architectures at scale
• Strong knowledge of deep learning models and common model architecture such as transformer models
• Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch)
• Ability to work independently in a fast-paced, and come up with creative solutions to challenging problems
• Excellent communication (both written and verbal) and presentation skills
• Advantage: Knowledge of cybersecurity principles, attack vectors, and defense mechanisms

Who we are

DV is the leader in digital performance solutions, helping our advertiser and agency partners verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms.  Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com.

What you will do

You will lead a team of experienced Data Scientists while remaining deeply involved in the technical work.

This is a hands-on leadership role (~70% hands-on) combining direct modeling work with ownership of team direction and execution.

You will work on core systems that operate at a massive scale, where:

• Data is abundant, but labels are scarce and expensive

• problems are long-tail and ambiguous

• Systems must meet strict latency and cost constraints (pre-bid)

Your responsibilities include:

• Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps

• Design and build models across computer vision, NLP, and multimodal pipelines

• Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment

• Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)

• Improve model quality (precision/recall) while balancing cost, latency, and scale

• Drive automation systems (auto-labeling, auto-curation, retraining loops)

• Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems

• Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward

• Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Who you are

• 3+ years of experience leading Data Science / ML teams

• 6+ years of hands-on experience in Machine Learning / Deep Learning

• Strong background in Computer Vision and/or NLP

• Experience building and deploying production ML systems at scale

• Strong understanding of real-world trade-offs (accuracy, cost, latency)

Technical requirements

• Hands-on experience with deep learning frameworks (PyTorch / TensorFlow)

• Experience with ML/DS tools (scikit-learn, OpenCV, HuggingFace, etc.)

• Experience working with large datasets and model evaluation pipelines

Advantages

• Experience with multimodal systems (vision + text + audio)

• Experience with LLMs / embeddings / foundation models

• Experience with AutoML, active learning, or data-centric AI

#Hybrid#
 

We offer the industry’s only platform that fuses customer identity and anti-fraud solutions – customer identity management, identity verification, and fraud prevention. 

We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.

About the Role:

As the AI Backend engineer  at Transmit Security, you will join a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. You’ll utilize technical skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.

This role requires both strategic thinking and hands-on expertise. You’ll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.

What you’ll do:

• Design, develop, and maintain backend services for AI agents and tool integrations using latest technologies
• Build scalable APIs and microservices that interface with LLMs and AI frameworks
• Implement agent orchestration systems, tool calling mechanisms, and workflow engines
• Optimize performance and reliability of AI-powered applications at scale
• Develop data pipelines for training, evaluation, and monitoring of AI systems
• Integrate with various LLM providers (OpenAI, Anthropic, etc.) and manage API interactions

What you’ll need:

• Excellent coding skills in Python/TypeScript, with at least 5 years of hands-on experience building reliable backend services, agents and tooling. Familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) is a strong advantage.
• Experience designing, deploying, and maintaining production systems that integrate ML components, including APIs, microservices, model serving layers, feature pipelines, monitoring, and CI/CD/MLOps workflows.
• Solid experience with AI related contexts Understanding of prompt engineering and LLM optimization techniques, RAG architecture
• Solid understanding of distributed systems concepts, performance optimization, observability, and operating services at scale.
• Strong communication skills, with the ability to bridge technical, product, and business perspectives.
• Prior experience in cybersecurity, fraud prevention, or identity management is a plus, especially with secure system architectures or ML-augmented decisioning systems.

Advantages

• Experience integrating with LLM APIs (OpenAI, Anthropic Claude, etc.)
• Experience with agent frameworks (LangChain, LlamaIndex, AutoGPT)
• Background in ML/AI concepts and model deployment
• Experience with message queues (RabbitMQ, Kafka) and event-driven architectures
• Experience with function calling and tool use patterns in LLMs

#LI-AM1 #LI-Hybrid 

#LI-TL1 #LI-Hybrid