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. Responsibilities: Own the development, qualification, and deployment of advanced metrology applications for 3D NAND process development, with primary emphasis on Focused Ion Beam (FIB) and one or more of the following: Atomic Force Microscopy (AFM) Optical interferometry or White Light Interferometry (WLI) Scanning Electron Microscopy (SEM) Semiconductor electrical or non-contact characterization methods Develop and implement innovative metrology solutions utilizing FIB, AFM, SEM, and related characterization techniques to close inline detection gaps and accelerate process learning. Lead the evaluation, qualification, and deployment of next-generation metrology systems and First-of-a-Kind (FOAK) technologies, including assessment of measurement capability, accuracy, repeatability, throughput, automation, and manufacturing readiness across FIB, AFM, SEM, and other advanced metrology platforms. Establish and drive technology roadmaps, ensuring alignment with future NAND technology requirements while fostering strong technical partnerships with equipment suppliers and industry collaborators. Identify and develop modeling opportunities using metrology, defect detection, artificial intelligence (AI), and machine learn

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Corporate Security Engineer, you'll help secure the systems GitLab team members rely on every day across a fully remote environment. This role sits within Corporate Security Engineering and focuses on building secure-by-default controls for endpoints and the SaaS platforms that support them, with a strong emphasis on macOS. You'll own meaningful technical decisions around endpoint hardening, automation, and detection, and you'll help turn security requirements into scalable engineering systems that are measurable, auditable, and designed to reduce friction for end users. This is a strong fit if

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. As Data Analysis Engineering Intern at Micron, you will learn about the exciting field of semiconductor failure analysis, using state of the art solutions to improve next generation memory solutions. The goal of this internship is to accelerate the cell cycles of learning by developing inline prediction to end of line cell performance using machine learning. We need engineers who are passionate about detecting problems and making changes for the better, and seek out innovative ways in how predict what will happen. We will assign you project to develop critical thinking and problem-solving skills. Your research tasks are designed to optimize and improve predictability of cell performance. Through this project we will provide the opportunity for you to collaborate with others from process integration, process engineering and data science. At the end of the period, we want you to have a deep understanding of the processes, device operation, and measurement strategies used in today’s semiconductor yield analysis department. Responsibilities: Review and analyze experimental data looking for device performance shift Possess a continuous improvement process (CIP) mentality, looking for ways to improve measurement accuracy and make a difference today! Recognize, identify, and raise awareness of process anomalies with the motivation of "who needs to know this now!" Use the data collected inline to drive process improvements Work with new detection tools and inspection strategies to loca

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. The Advanced Packaging Technology Development (APTD) department at Micron Technology is at the forefront of innovation, driving the advancement of memory and storage Interconnects and Packaging solutions that transform how the world uses information. Micron is dedicated to developing innovative processes and technologies that enable the creation of next-generation semiconductor products which drive the AI revolution. By collaborating closely with our global R&D, equipment and materials suppliers, and manufacturing teams, we ensure the efficient development, transfer and implementation of new technology nodes, maintaining Micron's leadership in the industry. As a Realtime Defect Analysis (RDA) Technology Development Engineer in APTD, you will learn how to use pioneering defect detection equipment and processes to solve issues and drive improvement. The goal of this position is to accelerate cycles of learning and technology transfer in Technology Development (TD). We're seeking an engineer who is passionate about creative problem solving and finding innovative solutions. This position will provide the opportunity for you to collaborate with engineers in process integration, process development, data science, and yield analysis within and outside of TD. Your ideas will impact the team globally! We need someone who will investigate process anomalies through root-cause analysis, data manipulation, and correlations. You will be expected to support experimentation, data analysis, baseline health metrics, and systema

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. The Advanced Packaging Technology Development (APTD) department at Micron Technology is at the forefront of innovation, driving the advancement of memory and storage Interconnects and Packaging solutions that transform how the world uses information. Micron is dedicated to developing innovative processes and technologies that enable the creation of next-generation semiconductor products which drive the AI revolution. By collaborating closely with our global R&D, equipment and materials suppliers, and manufacturing teams, we ensure the efficient development, transfer and implementation of new technology nodes, maintaining Micron's leadership in the industry. As a Realtime Defect Analysis (RDA) Engineer in APTD, you will learn how to use pioneering defect detection equipment and processes to solve issues and drive continuous improvement. The goal of this position is to accelerate cycles of learning and technology transfer in Technology Development (TD). We're seeking an engineer who is passionate about creative problem solving and finding innovative solutions. This position will provide the opportunity for you to collaborate with engineers in process integration, process development, data science, and yield analysis within and outside of TD. Ideal candidates will investigate process anomalies through root-cause analysis, data manipulation, and correlations. You will be expected to support experimentation, data analysis, baseline health metrics, and systematic and random defect improvement. Your ideas will impact the team glo

Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $100m in revenue and is the leading specialized storage cloud - managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We are seeking a Sr. AI Security Engineer to join our team! About The Role Backblaze is seeking a Senior AI Security Engineer to design and implement safeguards for internal AI usage , with a focus on agentic systems, developer protection, and runtime security . This is a hands-on role for a practitioner who has built and deployed security controls , not just defined policy. You will enable teams to safely use AI by creating enforcement layers, identity controls, and detection capabilities that constrain and monitor AI-driven activity. What You’ll Do: Agentic AI Safeguards Architect and implement guardrails for tool-using AI systems , including: Tool access controls and allowlists Context and memory isolation Step-level validation of agent actions Apply mitigations aligned to the OWASP Agentic AI Top 10 (e.g., prompt injection, unsafe tool use, data leakage, excessive autonomy) Runtime Security Controls Build enforcement mechanisms that govern AI behavior at execution time: Interceptors, proxies, or middleware for tool/API calls Policy decision and enforcement laye

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox, we strive to connect a billion people with optimism and civility, and the Safety organization’s mission is to become the leader in civil immersive online communities. We systematically detect, remove, and prevent problematic accounts, content and behavior, and we make Roblox accounts secure and free from compromise. We cover a broad area of the tech spectrum, including machine learning, classifiers for 3D models, experimentation, automation, detection workflows, and AI-powered text filters. Aligned and partnering with product teams, we use this tool-belt to discover new opportunities, influence and shape the product roadmap and prioritization, build safety products, and measure the impact on our community of users and developers. In doing so, we keep Roblox safe, civil, and inclusive, and we foster positive relationships between people around the world. WHY Safety Data Infrastructure To pro-actively find bad actors and protect good users, Roblox needs to ingest enormous amounts of data and make it usable both to our automated detection systems and for human moderators and customer support agents doing investigations. The Safety Data Infrastructure team is addressing these needs w

About the Team The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework . Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). What You’ll Do Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). Diagnose false positives and fa

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. Develop automation and detection tooling to continuously identif

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About this role We’re hiring experienced performance engineers to make performance measurement at Supabase rigorous, repeatable, and actionable by product teams. This role owns the benchmarking and profiling systems we use to detect regressions, explain performance changes, and publish credible numbers for customers and the market. You’ll build the tooling and the methodology and make it easy for product teams to use it correctly. You’d join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There’s no legacy process to inherit — you’ll help define how we measure and communicate performance metrics at Supabase. What you’ll do Build and evolve benchmarking, profiling, and load-testing tooling (cloud, database, and end-to-end). Define benchmark suites and reference workloads that reflect real customer behavior (and evolve them as the products change). Establish performance baselines and regression gates across products (variance tracking, environment control, and detection of changes). Build mechanisms that turn benchmark results into action: triage workflows, owner routing, and clear, reproducible reports. Partner closely with database teams (e.g. Multigres, OrioleDB) to identify bottlenecks and land concrete performance improvements. Enable the company to publish credible, repeatable performance numbers for customers and the market. Help teams self-serve performance testing and make performance a first-class engineering concern. Problems you might work on Build our continuous benchmarking infrastructure so product teams can spot performance regressions early. Ideally, teams can run benchma

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 a Staff Detection Engineer to join our team. This is a Hybrid role, reporting to the Senior Manager in the Threat Hunting department. You will analyze emerging threats, adversarial behaviors, and tactics, techniques, and procedures (TTPs) to understand attacker methodologies and improve detection capabilities across our global ecosystem. This role requires conducting proactive and retroactive threat hunting using Zscaler telemetry while working flexible schedules, including weekend night shifts, to meet global operational demands. What you’ll do (Role Expectations) Pick the handful of numbers that tell you the area is healthy (fidelity, false-positive and false-negative rates, ATT&CK coverage, detector regressions) and do the work to move them in the right direction Take what threat intel, hunts, and the analysts consuming your alerts tell you and turn it into what gets fixed and built next Lead

RDQ426R282 Databricks is building the world's best and most secure platform for data and AI. We innovate and deploy industry-leading solutions in security, compliance, and governance. As a member of the Trust and Safety Data Science team, you will work on projects critical to ensuring the security and compliance of the Databricks Platform. Our customers depend on Databricks to keep their data safe, all while orchestrating millions of virtual machines across three clouds in dozens of regions around the globe. Our engineering teams build highly technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is critical to making customers successful on our platform. We serve many companies with varying security and compliance needs. To efficiently serve these markets, we need to understand how customers use our existing features. This requires data-driven analysis of all aspects of security programs at Databricks. Customers also trust Databricks with their most valuable data and we have the mission to build the most trusted data analytics and ML platform in the world. We’re looking to expand our Trust and Safety Data Science team. You will join a group of “full stack” data scientists who partner with engineering and security teams, focusing on strategic plans that make Databricks secure and safe for our customers. The team will use statistical and machine learning techniques for fraud and abuse detection on our platforms using state of the art methods . You can read more about some of our efforts in this blog post . The work in fraud and abuse detection is dynamic and essential, offering an opportunity to make a substantial impact in maintaining the security and efficiency of business operations. More information is available at https://www.databricks.com/trust . The impact you will have: You will develop and implement Machine Learning mod

Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. About the Role We’re looking for a S enior Infrastructure Engineer to improve reliability and stability of Webflow’s customer-facing, production infrastructure, serving millions of page views per hour. Our product is used by over 2 million users world-wide across 190 countries, and you’ll help ensure our platform is secure and scalable for these users as tens of thousands of projects are launched on Webflow each month. Location: Remote-first (Argentina) Permanent, full-time employee (this is not a contractor position) Application Information: Application deadline: applications accepted on an ongoing basis until position is closed and filled This posting is for a new position. As an Senior Infrastructure Engineer you will: Own and evolve the cloud platform that Webflow's product and engineering teams depend on, including our compute layer, EKS fleet, serverless infrastructure, networking, and cloud operations across AWS and GCP. Help design and maintain our infrastructure-as-code foundation, evolving the patterns and shared components other teams build on. Design and maintain the networking layer that connects Webflow's services, ensuring reliability, security, and scalability across our cloud environments. Help make observability data the foundation of how we operate, improving the dashboards, alerts, and SLOs for the infrastructure you own so that issues are caught before customers notice, and on-call pages are actionable instead of noisy. Build and maintain AI-powered automation that improves how we manage cloud infrastructure, from policy-as-code and drift detection to LLM-assisted runbook generation. Help define the culture of this growing team as

Join Adobe Security Engineering and help build the ML and generative AI capabilities that protect Adobe, our products, and our customers. Our team sits where cybersecurity, large-scale data, and AI meet, building models for anomaly detection, threat detection, investigation, and security analytics across some of Adobe's largest datasets. As a Staff Machine Learning Engineer, you'll design, build, and scale production ML systems spanning deep learning, behavioral modeling, embeddings, and agentic AI. You'll write code, train models, run experiments, and help shape the architecture the broader team builds on. You'll also partner closely with data, platform, and security engineers across Adobe. The Challenge Architect end-to-end ML systems for high-volume security data, turning experiments into reusable capabilities. Own the ML lifecycle, from feature engineering through training, deployment, monitoring, and retraining. Build LLM and agentic AI capabilities for security investigation, including retrieval-augmented generation. Design evaluation frameworks that measure model quality and help analysts trust and validate results. Work with data and platform engineers to scale pipelines and resolve system bottlenecks together. Mentor engineers and help guide technical direction through design reviews and hands-on collaboration. What you bring Experience running production ML systems from early experimentation through sustained operation at scale. A strong background training models with PyTorch and transformers, including behavioral modeling and anomaly detection. Comfort with distributed compute like Spark, cloud platforms like AWS, and MLOps tools like MLflow. Experience building with LLMs or generative AI, along with evaluating how they behave in production. Strong Python and SQL skills, and solid software engineering habit

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role AI and machine learning are reshaping how developers debug, monitor, and ship software, and Sentry is uniquely positioned to lead that shift. We sit on a novel and massive dataset of real production errors, spans, and logs from tens of thousands of engineering organizations — the kind of signal that makes ML genuinely useful, whether it's a clustering model that groups related issues, a ranking system that surfaces the right alert at the right time, or an agent that proposes a fix. We're looking for an Engineering Manager to lead and grow our Machine Learning Engineering team. This team owns the full spectrum of ML at Sentry: classical techniques like clustering, ranking, anomaly detection, and embeddings that quietly power core product surfaces today, alongside the LLM-based and agentic systems shaping where the product is headed. You'll partner closely with product, design, and engineering leaders to decide where ML belongs in our products, what kind of ML actually fits the problem, and how we translate that work into experiences millions of developers rely on every day. In this role you will Set technical direction across the team's full ML surface area — from classical models for clustering, ranking, and anomaly detection to LLM-based and agentic systems — and make sharp calls about which approach fits each problem Define how the team evaluates and monitors ML systems in production, from offline metrics to online experimentation to model and agent observability Stay hands-on enough to review code and model designs, contribute to architecture discussions, and unblock engineers on complex ML problems Define