Detection And Response Jobs

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department Silicon Design Validation Project Title AI-Enabled NAND Silicon Design Validation and Report Automation Project Description This engineering internship provides the candidate with structured learning and practical exposure to silicon design validation for NAND flash memory products. The intern will learn NAND operations, circuit and feature validation principles, Verilog simulation, validation data collection, and engineering data analysis. Through a defined project assignment, the intern will develop a customized validation plan for a selected NAND feature or design circuit. The intern will also explore the use of Python, Generative AI, Large Language Models, AI Assistants, and Agentic AI solutions to improve the efficiency and accuracy of validation data collection, anomaly detection, analysis, and report generation. The project is developmental and project-based. Activities will be conducted under engineering guidance and within the approved project scope. Objective of the Project The objective is to develop the intern’s understanding of NAND silicon design validation while creating an AI-Enabled solution that improves the efficiency, consistency, and accuracy of validati

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team Our Network Enablement and Access team’s mission is to unlock the potential of the Plaid network by broadening and deepening our connection to data partners. We do this by providing solutions that allow our data partners to be part of the network and by providing best in class connections. By expanding and improving our connections to data providers, we are able to strengthen the Plaid network while also enabling great products and experiences. Plaid's data access platform owns the deep-infrastructure layer that determines how reliably and efficiently data flows from our data providers to our customers. As the data supply network evolves, we are building the new platform capabilities that keep it strong: ensuring that our traffic stays smooth for the providers we depend on, building improved detection capabilities that enable us to catch issues as they happen, and evolving our data access toolkit to be more efficient over time. About the role: You will decide what data Plaid goes after next. Bank data got us here, but the picture our customers need now includes things we do not have: property tax, merchant and SKU-level purchases, utilities, tax, payroll. Some of it

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Join Micron as a Senior Manager, Logistics Security Program, where you will have the outstanding opportunity to lead a world-class global security initiative! This role is critical in ensuring the flawless implementation of our logistics security strategy, encouraging collaboration with key partners, and advancing our program to new heights. Responsibilities: Direct Micron’s worldwide logistics security initiative for valuable shipments, establishing strategy, governance, standards, controls, and performance expectations throughout the transportation network. Lead and expand a distributed team of logistics security experts while promoting uniform performance across Asia Pacific, the Americas, Europe, and other priority regions. Maintain a risk-based shipment security framework that assesses lane, geography, modality, theft history, business impact, recovery capability, and other key risk factors. Establish and enforce logistics provider security requirements, including cargo tracking, route compliance, geofencing, chain of custody, tamper detection, monitoring, blocking issue, and recovery protocols. Partner multi-functionally with Procurement, Logistics, Global Security, Legal, Risk, Finance, and business collaborators to integrate security requirements into contracts, procedures, governance, and scorecards. Coordinate logistics security vendors and providers, including selection, performance management, service levels, monitoring operations, recovery capabilities, and corrective ac

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Department F10 Manufacturing, Photolithography Project Title Internet of Things-Based Photolithography Equipment Monitoring and Anomaly Detection Project Description The intern will undertake a structured engineering project focused on developing an Internet of Things-based solution for photolithography equipment and process monitoring. Under the guidance of experienced engineers, the intern will study photolithography equipment behaviour, process flow, and available sensor signals. The intern will apply Python programming, data analytics, system integration, and selected Machine Learning techniques to develop or enhance a defined monitoring use case. The project will provide practical exposure to semiconductor manufacturing equipment, Internet of Things architecture, data ingestion, signal processing, visualization, and AI-Enabled anomaly detection. Project activities will be limited to the assigned use case and conducted with appropriate engineering guidance. Objective of the Project Develop a strong understanding of photolithography equipment behaviour, process flow, and process signals. Design and implement an Internet of Things-based solution for enhanced equipment or process monitoring. Ena

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location MSB, Singapore (990 Bendemeer Road) Department MSBH Facilities Project Title AI-Powered Sustainability Command Center Project Description The intern will undertake a structured engineering project focused on developing an AI-Powered Sustainability Command Center for selected energy, water, utility, cost, and carbon datasets. Under the guidance of experienced engineering and digital professionals, the intern will assess existing data sources and reporting processes, develop a structured and reliable data model, and create an interactive dashboard for sustainability performance monitoring. The project will also explore analytics, Artificial Intelligence, Generative AI, and automation methods for anomaly detection, insight generation, opportunity prioritization, and reporting. AI-generated outputs will remain traceable to source data and subject to appropriate engineering validation. Objective of the Project Consolidate agreed sustainability and utility datasets into a structured and reliable data model. Develop an interactive command-center dashboard for operational and management visibility. Apply rule-based analytics or AI-Assisted methods to identify anomalies

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for an Insider Risk Security Engineer to join our team. This is a Remote (United States) role, reporting to the Senior Architect in the Enterprise Security Dept department. Serving as a senior contributor on the Insider Risk program within Enterprise Security, you will take operational direction from the Insider Risk Team Lead while operating with high ownership to refine playbooks, lead detection engineering, mentor junior analysts, and represent the team with HR, Legal, and executive stakeholders. What you’ll do (Role Expectations) Sharpen the Insider Risk Program’s detection capabilities by refining rules to reduce noise, close coverage gaps, and surface high-fidelity alerts in adequate time Perform endpoint and user activity investigations using EDR/XDR, UEBA, and SIEM tools, managing cases end-to-end to create factual timelines Drive the development and iteration of insider Risk investigation playbo

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. About the Role Hybrid (3 days per week in the London office required) Individual contributor role Every day, millions of customer transactions flow through our platform. Our challenge is to make payments effortless for genuine customers while preventing fraud, abuse, and financial loss. As the Senior Strategy & Operations Manager for Payments Risk & Fraud, you'll own one of our most commercially important problem spaces. You'll define the strategy for payment fraud, promotions abuse, cash risk, and chargebacks – balancing customer experience, growth, and profitability. This is an end-to-end ownership role. You'll identify opportunities, shape strategy, influence product and engineering roadmaps, partner with data science to improve detection models, and work closely with Finance and Payments to protect revenue while enabling sustainable growth. If you enjoy solving ambiguous, high-impact business problems using data, technology, and cross-functional leadership, we'd love to hear from you. What You'll Own Defining our Payments Risk Strategy Own the strategy and roadmap for payment fraud, promotions abuse, cash risk, and disputes across multiple markets. Identify emerging risks, prioritise investments, and continuously evolve our controls to protect customers and the business while supporting growth. Driving Commercial Performance: Own the key business metrics that matter, including: Fraud losses Chargeback rates Payment approval rates Promotions efficiency Recovery rates False positive rates Evaluate trade-offs between risk, customer experience, and conversion to maximise long-term profitability Building Data-Driven Solutions Use data to understan

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Technical Architect: Company Description Okta is the leading independent identity partner. We enable organizations to securely connect the right people and technologies, providing identity solutions that protect workforce and customer identities across a rapidly evolving technology landscape. The P0 Threat Research organization operates at the intersection of adversary research, threat hunting, detection engineering, data science, and product innovation. Our mission is to understand modern adversaries better than anyone else and make that knowledge actionable for our customers and products. Position Description Architect, Threat Research will help define and drive the technical vision for Okta's threat research efforts. This role is focused on understanding how modern adversaries operate, developing new methodologies for discovering and analyzing attacker behavior, and translating that research into actionable outcomes for our customers and products. Initial areas of emphasis include identity, cloud, SaaS, AI, and other emerging technologies, but success in this role is rooted in deep threat research expertise and the ability to rapidly develop expertise in new technologies and attack surfaces. The Architect will serve as a senior technical leader within the Threat Research organization. This individual will work closely with threat researchers, threat hunters, detection engineers, data scientists, product teams, engineering teams, and other senior t

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Everpure's growth depends on data our teams can actually trust. As Sr. Manager, Master Data Management & Data Governance, you'll own the enterprise vision for our most critical data domains — Customer, Product, Asset, and Vendor — and build the governance foundation that makes every downstream decision faster and better informed. You'll build the stewardship model and the team around it as the function grows, and use AI and automation to move master data quality from periodic cleanup to continuous, self-correcting control. Partnering with leaders across Sales, Finance, Operations, Product, and IT, you'll turn fragmented data into an AI-ready asset the whole company can build on. This is a highly visible role with a direct line to how Everpure runs. WHAT YOU'LL DO Set and execute the enterprise strategy for Customer, Product, Asset, and Vendor master data, defining the governance and stewardship models that keep these domains consistent and trusted across every system that touches them. Deploy AI and automation across matching, deduplication, classification, enrichment, and remediation, shifting master data quality from manual cleanup to continuous monitoring, anomaly detection, and automated correction. Build the AI-ready data foundation, institutionalizing lineage, catalogs, dictionaries, and metadata, and ensuring master data flows cleanly across ERP, CRM, PLM, service management, and analytics platforms. Es

About the Role: We are looking for a Senior DevOps Engineer to join our DevOps team at K Health. You will own and evolve the infrastructure underpinning a healthcare AI platform serving patients and enterprise health system partners. This is a high-ownership role: you will architect and operate cloud environments across K Health and its enterprise partners, lead complex infrastructure migrations, drive disaster recovery programs, and help build the next generation of AI-powered operations tooling. You will also mentor junior engineers and collaborate closely with product and engineering teams across the company. This is a hybrid role based in New York City (4 days/week in office) and includes participation in a daytime on-call rotation. What you will do: Own the design, implementation, and evolution of our GKE-based Kubernetes infrastructure across K Health and enterprise partner environments. Build and maintain our Terraform modular infrastructure library, including reusable modules with automated testing, across GCP, Cloudflare, and AWS. Architect, build, and maintain GitLab CI/CD shared pipeline templates used by all engineering teams (build, test, security scanning, deployment). Own and maintain self-hosted infrastructure software running in-cluster, including GitLab, ArgoCD, Langfuse, DependencyTrack, NGINX Ingress, and others. Implement and support security and compliance controls across infrastructure and the software supply chain - secrets management, pipeline secret detection, container scanning, SOC2 and HIPAA. Drive disaster recovery readiness: design failover scenarios, author runbooks, and lead periodic DR tests. Lead development of AI-powered operations tooling and agentic infrastructure. Monitor, troubleshoot, and improve production system reliability; respond to incidents during on-call shifts. Mentor junior DevOps engineers and establish team-wide engineering standards. What we are looking for: 5+ years of experience in DevOps, platform engineering,

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI Example Projects: Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing bi

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI Example Projects: Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing bi

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Every industry is moving AI to the center of operations, but there is still no clear blueprint for getting from pilot to profit. That is the problem our engineers work on. As a New Grad Software Engineer, you will own meaningful, customer-facing work from day one — shipping products, talking directly to the customers who use them, and iterating fast. Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI Example Projects: Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/U

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Every industry is moving AI to the center of operations, but there is still no clear blueprint for getting from pilot to profit. That is the problem our engineers work on. As a New Grad Software Engineer, you will own meaningful, customer-facing work from day one — shipping products, talking directly to the customers who use them, and iterating fast. Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI Example Projects: Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/U

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model