We are looking for an experienced Applied Data Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform - designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops - enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productionize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

We are looking for an experienced Applied AI/ML Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform, designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

We're hiring an exceptional Applied AI Scientist to join our team!

In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across Tipalti's core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.


In This Role, You Will Be Responsible For


Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

We're looking for a Senior Data Scientist to join the AI cybersecurity team in the Security and Networking Architecture group. As a Senior Data Scientist youll have the opportunity to take an active part in the research and development of our world-class networking and data center security products. This role involves creative problem solving alongside engineering teams, and is key for the continued success of AI networking security.

What youll be doing:

Developing agentic AI systems for security, combining generative models, RAG, and tool-augmented reasoning to automate threat analysis and response workflows.

Optimizing and fine-tuning models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Developing, implementing and improving models and algorithms across media types, whether time series, images, text, audio or video.

Leveraging data pipelines to efficiently process and transform large volumes of data for training and inference purposes.

Applying alignment techniques and parameter efficient fine-tuning to improve model performance.

Measuring and benchmarking model and application performance to drive improvements.

Driving the gathering, building, and annotation of domain specific datasets for benchmarking and training.

Collaborating closely with software and hardware engineers on new features and improvements. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Were looking for a Data scientist Expert to join us and spread our power. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems. 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 companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the 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.

Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.

This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.

Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.

This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.

Responsibilities
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights.
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes.
Work closely with product and engineering teams to translate business needs into scalable AI solutions.
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products.
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance.
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration.
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring.
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration.
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact.

We are looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through our companys SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.
This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.
Key Responsibilities
Lead the design, development, and deployment of AI/ML models that enhance our companys security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals.

We are looking for Senior Data Scientists who are excited about building real-world AI systems in production, not just experimenting with models, but using cutting edge tools and solutions for advanced evaluation of conversation threads, individual exchanges, agents, skills and tools in order to optimize the full product flow and directly impact customer experience.
Key Responsibilities
Design, develop, and maintain Evaluation pipelines for AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop and maintain scalable evaluation infrastructure, services, and tooling supporting GenAI applications in production
Improve LLMs, RAG pipelines, vector databases, and orchestration frameworks integrated into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.

We are seeking a Senior Data Scientist to join the team that builds the predictive intelligence powering the app. You will own the ML models behind user engagement, cardiovascular risk stratification, and personalized health recommendations - the systems that determine what users see, when they're nudged, and how their health trajectories are shaped.

This role demands both statistical depth and engineering proficiency - you will be expected to take models from research through to deployment, write code built for production, and use AI coding assistants fluently as part of how you get work done.

Responsibilities
Lead end-to-end development of predictive ML models. From data exploration and feature engineering through training, validation, deployment, and ongoing monitoring across engagement and clinical risk domains.
Apply strong statistical foundations to model design, feature selection, uncertainty quantification, and interpretation of results
Write production-grade Python code that is clean, tested, and built for maintainability and scale.
Use AI coding assistants to accelerate development, code review, and documentation without sacrificing quality or rigor.
Partner with product managers, data engineers, and software engineers to translate strategic questions and user behavior patterns into measurable, data-driven solutions.
Research and implement cutting-edge ML techniques spanning supervised and unsupervised learning, causal inference, deep learning, and reinforcement learning to tackle complex healthcare challenges.
Contribute to MLOps infrastructure: model serving, versioning, evaluation pipelines, and monitoring.
Design and interpret A/B tests and other experimental methodologies to measure the impact of models, features, and interventions.

we are looking for a Fraud Data Scientist.
As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.
In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.
What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.
Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.
Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.
Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.
Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.
Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.