Detection And Response Jobs

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe achieving this goal requires real-world deployment and continuous iteration based on how our products are used—and misused—in practice. The Child Safety team is responsible for detection, review, and enforcement of OpenAI’s Child Safety product policies. We leverage a balanced use of technology and subject matter expertise to scale our operations. We collaborate with internal legal, research, and policy teams, external experts, and other industry stakeholders to keep OpenAI aligned with evolving regulations and industry best practices around child safety. About the Role As a Child Safety Enforcement Specialist on the Intelligence & Investigations, you independently lead defined child safety investigations and projects from triage through documented outcome. You apply strong working knowledge of policy and investigative practice, surface trends in abuse signals, recommend evidence-based mitigations, and coordinate with partners to deliver reliable safety outcomes. The role includes sensitive content review and may involve supporting quality and workflow improvements. You’ll be responsible for: This role supports child safety investigations, enforcement, reporting, and process improvement. The work includes significant review of sensitive content and analysis of user behavior. This role independently owns defined projects, aligns with cross-functional priorities, and escalates complex legal or policy questions through established channels. In this role, you will: Independently review and investigate child safety content and behavior, including CSAM and grooming signals, applying policy consistently and documenting evidence and rationale. Lead well-defined high-risk escalations end to end; anticipate blockers, communicate progress, and make or recommend enforcement decisions within policy and escalation boundaries. Identify potential mandat

Titan Security is built on serving our clients and building careers – just like yours. We are trusted by some of the most well-known companies and properties in the country while remaining dedicated to building personalized security solutions that solve the needs of every customer we support. Named as a nationally recognized Top Workplace in 2024 and 2025 by USA Today, Titan's customized approach to security services will provide you with the opportunity to learn, grow and succeed. Our core values of being Unified, Transparent, Innovative, Committed and Accountable help us in providing unparalleled service and support in all that we do. If you are looking for a meaningful career, a culture of excellence, and the ability to make a difference, we want to talk to you! Titan Electronics is the technology and systems integration arm of Titan Security Group, a leading security solutions provider servicing millions of square feet across commercial, residential, institutional, and industrial properties. Specialized in designing, installing, and servicing advanced electronic security architecture, Titan Electronics delivers customized, enterprise-grade solutions tailored to complex facility environments. We are seeking an experienced Level III Security Systems & Low Voltage Field Technician to lead installations, testing, programming, and complex troubleshooting for commercial, industrial, and high-security clients. In this senior-level role, you will handle advanced integration of Access Control, IP Video Surveillance (CCTV), Intrusion Alarms, and Structured Cabling systems. You will also serve as a technical mentor to Level I & II technicians and act as the primary on-site point of contact for project managers and clients. Key Responsibilities System Installation & Integration: Mount, wire, program, and commission advanced commercial security systems including IP CCTV/NVRs, Access Control (ACS), Intrusion Detection, Intercoms, and Gate systems. Network & So

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Observability engineering team builds and operates the systems that give us deep visibility into the health, performance, and efficiency of our platform. From metrics, logs, and traces to cost attribution and budgeting, this team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability and spend. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, and the agents and operators that power telemetry collection—while continuously raising the bar on signal quality and operational clarity. This team ensures that engineers across Figma can detect issues quickly, understand system behavior at scale, and make informed decisions about reliability. The team owns and evolves our core observability stack—including platforms like Datadog, shared instrumentation libraries, the agents and operators that power telemetry collection, and a host of internally developed components to power AI Trace Observability —while continuously raising the bar on signal quality and operational clarity. As the Engineering Manager for Observability, you will lead a team of five engineers responsible for shaping the future of visibility and efficiency at Figma. You’ll define the strategy for instrumentation standards and cost transparency, drive initiatives to optimize observability footprint and spend, and explore innovative AI-driven approaches to anomaly detection

Titan Security is built on serving our clients and building careers – just like yours. We are trusted by some of the most well-known companies and properties in the country while remaining dedicated to building personalized security solutions that solve the needs of every customer we support. Named as a nationally recognized Top Workplace in 2024 and 2025 by USA Today, Titan's customized approach to security services will provide you with the opportunity to learn, grow and succeed. Our core values of being Unified, Transparent, Innovative, Committed and Accountable help us in providing unparalleled service and support in all that we do. If you are looking for a meaningful career, a culture of excellence, and the ability to make a difference, we want to talk to you! Titan is expanding its Titan Electronics (Security Integration) division in Austin and is seeking a high-performing, hunter-oriented Business Development Manager to drive net-new revenue growth . This is a true new business role focused on: Building pipeline from scratch through field prospecting and relationship development Winning complex, consultative security integration deals Leveraging Titan’s unique position as both a guarding and technology provider This individual will not only hunt new logos , but also strategically cross-sell electronic security solutions into Titan’s existing guarding customer base , unlocking a significant competitive advantage. Key Responsibilities New Business Development (Hunter Focus) Prospect, qualify, and close net-new business for integrated security solutions: Video surveillance- VMS, IP Cameras, Cloud, AI Access control systems Intercoms, intrusion detection, and related technologies Execute disciplined outbound strategies: cold calling, onsite visits, networking, and events Build and maintain a robust, self-generated pipeline Target key verticals including: Commercial real estate Corporate campuses Logistics & distribution Retail High-end residential comm

We are looking for a Trading Operations Specialist to support our algorithmic trading activities. Your main responsibility will be to ensure that trading runs smoothly, reliably, and safely, through careful execution of operational checks, real-time monitoring, and timely escalation. This is a hands-on role, not a management track - ideal for someone detail-oriented, disciplined, and motivated to work in a regulated algo-trading environment What You’ll Be Doing: Execute pre- and post-session checks to confirm system readiness and close out procedures Monitor intrasession invariants (positions, connectivity, latency, market data consistency, error rates) and promptly escalate deviations Follow escalation procedures to involve the right people at the right time when anomalies arise Contribute to continuous improvement of anomaly detection quality, incident reaction times, and communication efficiency Keep accurate operational records and logs for auditability and learning Shift-based schedule, ensuring reliable coverage across required trading hours. What We Look For In You: Bachelor’s degree in Finance, Economics, Mathematics, or related field (or equivalent practical experience) 3 years in trading operations, trade support, or market surveillance (experience in algo/electronic trading is a plus, but not required) Solid understanding of how financial markets and trading systems operate High attention to detail and ability to stay calm under pressure Comfortable following structured procedures while also spotting where they can be improved Clear communicator in English, able to escalate effectively and work with multidisciplinary teams Why Should You Join Our Team? Join an international team of highly qualified professionals Work remotely from an eligible location within the UTC−11 to UTC−5 time zone range. 40 paid days off Competitive salary

Who we are About the team The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns 10+ real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates directly into dollar impact for Stripe and its users. The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. Radar is growing fast, and the team is actively building new products like defenses against AI token theft, free trial abuse, and programmatic attacks. What you'll do In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch. Responsibilities Design, build, train, evaluate, deploy, and own ML models in production that detect fraud across Stripe’s global payments network Design and build large-scale ML systems that operate on diverse and large scale data Experiment and iterate on ML models to achieve key business goals around data quality and accuracy Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliability Collaborate with product, data science, and engineering partners across Stripe to identify opportunities where ML can improve outcomes for merchants and consumers Engage with the latest ML/AI developments and take calculated risks in transforming innovative ideas into productionized solutions Mentor engineers and contribute to a strong ML engineering culture within the team Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are enco

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for an experienced Machine Learning Engineer to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Machine Learning Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform - one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: Python / Postgres / Snowflake / dbt AWS SageMaker and MLflow What you'll do: Own and drive the foundational work of a ML system at CLEAR Design, build and deploy ML models for various applications, such as document and image processing, fraud detection. Develop and implement robust data pipelines at a variety of scales, including collection, pre-processing, transformation, and feature engineering Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 3+ years of experience building, operating and scaling ML models for consumer applications, particularly those with experience building end-to-end systems Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Expertise in best practices for feature enginee

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 the Product Quality Engineering PQA Sr. manager, your role involves ensuring that DRAM products shipped from Micron Taiwan Frontend Manufacturing meet customer requirements in terms of performance and reliability. Simultaneously, you aim to minimize the overall Cost of Non-Conformance. In that, your responsibilities include for the comprehensive monitoring and analysis of probed wafers for potential Quality and Reliability risks and for the technical standard of the fail mode modelling on which the disposition decision is based. Collaborating with GQ and PE, you continuously improve product test coverage and setting of appropriate warning and screen limits to prevent escapes to Backend and Customer. Concurrently, your mission is to provide guidance for process improvements to enhance the baseline Probe-to-Ship yield and the overall ratio of prime Product Grading available for Micron shipment. In collaboration with Process QE and Fab Operation you assure the comprehensive Problem Solving of deviations that occur and seamless implementation of Preventive Actions and Shift-Left detection points. You also ensure that manufacturing process/equipment changes impacting products undergo a full risk assessment and qualification process by using AI methodlogy and solution. Responsibilities include but are not limited to the following: Define and maintain critical quality metrics aligned with business objectives Establish clear goals and aggressive timelines to achiev

Machine Learning Engineer – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like A

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About Enterprise Risk & Internal Audit The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth. About the Team We’re looking for an intelligent, driven professional to join our Model Risk Management (MRM) team. This team seeks to establish, maintain and oversee an effective MRM framework to identify, quantify, monitor, mitigate and report on model risk throughout the company. You will have an outstanding opportunity to work cross-functionally to develop a profound understanding of models that drive critical business decisions, and add value to the company by mitigating risks due to ineffective model design or model misuse. What You’ll Do Perform independent challenges of machine learning models used for credit underwriting, credit risk, and/or fraud detection through thorough validation and ongoing monitoring Identify model weaknesses and opportunities for improvement Collaborate with model owners to remediate model validation findings Partner cross-functionally to implement and maintain the company’s MRM framework Partner with Internal Audit, Internal Controls, and Compliance to ensure timely resolution of audit and regulatory requests What We Look For 4-6 years of professional experience in related technical areas such as model development, model validation, data science Deep and broad knowledge and experience in machine learning modeling, credit underwriting, credit risk management, and/or

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About Enterprise Risk & Internal Audit The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth. About the Team We’re looking for an intelligent, driven professional to join our Model Risk Management (MRM) team. This team seeks to establish, maintain and oversee an effective MRM framework to identify, quantify, monitor, mitigate and report on model risk throughout the company. You will have an outstanding opportunity to work cross-functionally to develop a profound understanding of models that drive critical business decisions, and add value to the company by mitigating risks due to ineffective model design or model misuse. What You’ll Do Perform independent challenges of machine learning models used for credit underwriting, credit risk, and/or fraud detection through thorough validation and ongoing monitoring Identify model weaknesses and opportunities for improvement Collaborate with model owners to remediate model validation findings Partner cross-functionally to implement and maintain the company’s MRM framework Partner with Internal Audit, Internal Controls, and Compliance to ensure timely resolution of audit and regulatory requests What We Look For 4-6 years of professional experience in related technical areas such as model development, model validation, data science Deep and broad knowledge and experience in machine learning modeling, credit underwriting, credit risk management, and/or

Machine Learning Engineer – Biometrics (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestra

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. The End User Protection Team Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers. We ensure access to applications is safe, secure, and seamless for the more than 100 million daily logins worldwide. Our modern approach to identity enables this Tier-0 global service to deliver convenience, privacy, and security, allowing customers to focus on innovation. The End User Protection team is responsible for building and maintaining Auth0’s Attack Protection capabilities. Cyberattacks, such as credential stuffing and password spraying, often target end users to gain unauthorised access to applications. These attacks pose a significant threat, compromising user accounts and data. The Attack Protection features mitigate these risks by continuously monitoring user login behaviour and automatically detecting and blocking malicious activity. They protect users without adding unnecessary friction. The team works closely with our Machine Learning and AI teams to develop and deploy cutting-edge detection models. This collaboration allows application builders to provide a secure login experience for their users while isolating them from the complexities and ever-evolving tactics of these attacks. The Software Engineer II Opportunity We are looking for a Software Engineer II to join our End User Protection team. What you’ll be doing Be a part of a fast-paced, agile team. Design and buil

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex