Staff Detection Engineer Jobs

We are looking for an experienced Senior or Staff Engineer for our SRE, InfraSec team, to guide the security of our cloud-based infrastructure. As a Staff SRE, you will be very hands-on technically while also mentoring a small team of SREs. The InfraSec team collaborates closely with other engineering teams to ensure that our infrastructure adheres to the highest security standards. They build essential security infrastructure and implement controls that reinforce the platform’s security posture. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions.This team is deeply involved in the technical aspects of security and the nuances of its actual implementation. This role can sit in our New York City, Austin, Seattle or San Francisco offices on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. Responsibilities: Cloud Security Design and Implementation: Help lead the design and deployment of security solutions for cloud platforms (AWS, Azure, GCP), including network and compute security, identity management, and cloud security posture management (CSPM) Automation and Monitoring: Build automated solutions for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection Security Tooling: Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM Qualifications: Experience: 6+ years of experience in SRE, infrastructure engineering or similar role, with a strong focus on security work, with ideally 2+ years in a senior or staff engineering role Security Mindset: A comprehensive understanding of all facets of cloud environment security, spanning from foundational OS networking laye

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. Responsibilities Data Pipeline Engineering: Build scalable ingestion pipelines for structured, semi-structured, and engineering data sources. Workflow Orchestration: Develop reliable batch, scheduled, and event-driven workflows using Apache Airflow and cloud-native services. ETL / ELT Frameworks: Implement reusable pipeline patterns, transformations, incremental ingestion, and data quality checks. Schema Management: Implement schema registry, schema versioning, schema evolution, and compatibility controls. Delta Detection: Build change detection and incremental refresh mechanisms for efficient large-scale data synchronization. Entity Extraction: Extract and normalize key identifiers such as Lot, Die, Wafer, Test, Flow, Product, and Step. Cloud Landing Zones: Set up secure AWS, GCP, and on-prem landing targets for validation and analytics pipelines. <

Perplexity is seeking a highly skilled, experienced and hands-on Offensive Security Engineer to join our dynamic security team, taking an adversarial approach to hardening Perplexity's infrastructure, applications, and AI systems. You'll plan and execute red team operations, penetration tests, and attack simulations across our cloud infrastructure, web and mobile applications, AI/ML pipeline, and corporate environment—finding real vulnerabilities before adversaries do and working directly with engineering teams to drive remediation. Responsibilities Plan and execute red team and purple team engagements simulating advanced threat actors across cloud infrastructure (AWS, Kubernetes), endpoints, and application surfaces Conduct continuous penetration testing of web applications, APIs, mobile clients, browser extensions, cloud infrastructure, and internal services Assess AI/ML-specific attack surfaces including prompt injection, model exfiltration, agent abuse, tool-use exploitation, and MCP security boundaries Develop and maintain custom offensive tooling, exploits, and automation to improve the efficiency and coverage of security testing Perform open-scope adversary simulations that test detection and response capabilities end to end, collaborating closely with the defensive security team Drive threat modeling sessions with engineering teams to identify and prioritize attack vectors in new features and architectures Deliver clear, actionable findings to both technical and executive audiences; partner with engineering to validate remediations Contribute to the security of CI/CD pipelines, supply chain integrity, and secrets management through offensive assessment Stay current on emerging attack techniques, vulnerability research, and adversary tradecraft; bring external perspective into Perplexity's security strategy Qualifications 5+ years of hands-on experience in offensive security, red teaming, or penetration testing Deep technical expertise in at least two of: clo

RDQ127R9 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a Sr. Staff Software Engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you will have: Design and manage the Money system

RDQ327R179 While candidates in the listed location(s) are encouraged for this role, candidates in other (US) locations will be considered. About the Team The Agentic Security Engineering team is a horizontal, shared services engineering team that enables every Databricks security function AI-native. We enable building the AI agents, "personas," and own the shared platform that security teams across the org (Detection & Response, Threat Intelligence, Vulnerability & Product Security, Red Team, GRC, and Continuous Monitoring) build on to operate at machine speed, safely and reliably. We leverage AI to transform how security is done. The Role As a Senior Staff Security Software Engineer on the Agentic Security Engineering team, you will be a senior technical authority and architect for Databricks’ shared Security AI platform. You will define the platform architecture, technical standards, and multi-year engineering direction that allow security teams to build, deploy, and operate governed AI personas safely at scale. Your work will span secure agent identity, isolation and sandboxing, policy enforcement, auditability, observability, evaluation, orchestration, and reliable integration with Databricks and security infrastructure. You will operate across organizational boundaries, aligning engineering and security leaders on platform architecture, driving adoption of common patterns, and resolving complex technical problems that affect multiple security functions. You will influence the quality, safety, reliability, and velocity of the broader Security AI ecosystem without owning the domain logic or business outcomes of every individual persona. The Impact You Will Have Shared Security AI Platform Architecture Define and evolve the architecture for the shared Security AI platform and its paved road for governed agentic workflows. Establish reusable patterns for agent identity, least-privilege access, sandboxing, egress control, secret isolation, policy enforcement

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity Postman is seeking an experienced AI Systems Reliability Engineer to help define, build, and maintain the infrastructure and processes that ensure the reliability, scalability, and performance of Postman’s AI-powered API and agentic systems in production. This role focuses on monitoring, availability, incident response, and automation to support AI services and tools trusted by millions of developers globally. What You’ll Do Develop and manage reliability metrics (SLOs) for AI-driven API services and agentic AI platform features Implement comprehensive observability and monitoring systems for real-time performance and fault detection Design and drive automated failover, recovery, and incident response strategies for high-availability AI infrastructure Optimize resource utilization, particularly GPU/accelerator efficiency, ensuring cost-effective AI system operation Collaborate closely with engineering, platform, and product teams to align reliability efforts with broader organizational goals Lead efforts to build internal tooling and automation focused on AI system stability and operational excellence Drive continuo

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Department overview: The Senior Solutions Architect shapes the technical approach for moving employee technology support from reactive response toward predictive detection, safe self-healing, and higher value enablement. The role turns service needs into cross-platform architecture, reusable patterns, and clear implementation guidance. Working with engineering, operations, platform, security, and architecture partners, this individual makes technical tradeoffs visible and helps teams deliver solutions that can be operated and improved over time. What you’ll be doing: Architecture and technical direction Lead technical discovery for complex, cross-platform employee technology opportunities and define target architectures, integration patterns, and implementation options. Design the flow from service and endpoint signals through detection, diagnosis, approved remediation, escalation, and outcome recording. Set reusable standards for APIs, identity, data handling, observability, testing, rollback, and operational ownership in automation solutions. Assess build versus buy options and emerging AI capabilities against employee value, technical feasibility, security, and supportability. Platform architecture and integratio

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best Data Intelligence Platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping solve product and business challenges. The Data team also functions as an in-house, production "customer" that dogfoods Databricks and drives the future direction of the products. The impact you will have: Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights. Work closely with Engineering, Product Management, Sales and Customer Success to understand product usage patterns and trends and make data-driven decisions, recommendations a

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . What you’ll do: Be the technical lead for the forecasting team . Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale. Lead the full modeling lifecycle end to end : problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability. Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models. Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‑visibi

P-1489 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role As a Staff Technical Program Manager (TPM) for Trust & Safety Engineering, you will drive technical execution across infrastructure initiatives that protect platform integrity, user identity, and data privacy at scale. You will work directly with Security Engineering, Identity Infrastructure, Machine Learning, and Core Platform teams to design, build, and deploy systems for authentication, access control, and anomaly detection. Working embedded within engineering groups, you will translate identity protocols, privacy-by-design principles, and threat mitigation models into clear technical specifications, system dependencies, and actionable execution roadmaps. This role is focused on technical execution, resolving complex engineering dependencies, and delivering scalable systems that guarantee identity integrity and prevent platform abuse. Key Responsibilities Define, articulate, and own the security program strategy and roadmap, ensuring alignment with Databricks’ business and product goals. Drive initiatives across Identity Infrastructure, Data Governance, Platform Security, Machine Learning, and Trust Engineering. Oversee execution of complex security engineering multi-half initiatives (AuthN/AuthZ/Secret/PKI/Cryptography,etc), demonstrating ownership from strategy through outcomes. Leverage

P-1489 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems; from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role As a Staff Technical Program Manager (TPM) for Trust & Safety Engineering, you will drive technical execution across infrastructure initiatives that protect platform integrity, user identity, and data privacy at scale. You will work directly with Security Engineering, Identity Infrastructure, Machine Learning, and Core Platform teams to design, build, and deploy systems for authentication, access control, and anomaly detection. Working embedded within engineering groups, you will translate identity protocols, privacy-by-design principles, and threat mitigation models into clear technical specifications, system dependencies, and actionable execution roadmaps. This role is focused on technical execution, resolving complex engineering dependencies, and delivering scalable systems that guarantee identity integrity and prevent platform abuse. Key Responsibilities Define, articulate, and own the security program strategy and roadmap, ensuring alignment with Databricks’ business and product goals. Drive initiatives across Identity Infrastructure, Data Governance, Platform Security, Machine Learning, and Trust Engineering. Oversee execution of complex security engineering multi-half initiatives (AuthN/AuthZ/Secret/PKI/Cryptography,etc), demonstrating ownership from strategy through outcomes. Leve

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

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: The Imagine team is redefining AI-driven media experiences for Grok users worldwide. As a Product Safety Engineer on the Imagine team, you will build the critical safety systems and infrastructure that ensure Grok’s multimodal generation capabilities (images, video, audio, and beyond) are powerful, delightful, and responsibly deployed. You’ll design and scale safeguards, detection systems, and evaluation frameworks that prevent harm while preserving creativity and user freedom. Your work will directly shape how millions of users experience generative media — balancing rapid innovation with rigorous safety, trustworthiness, and alignment with SpaceXSI's mission. If you’re a driven engineer passionate about AI safety, content integrity, and building robust systems that protect users without stifling innovation, this is your opportunity to make a lasting impact at the frontier of multimodal AI. RESPONSIBILITIES: Design and implement scalable safety systems for Grok’s media generation platform, including real-time content moderation, risk detection, and safeguard enforcement for images, video, and audio. Build infrastructure to measure, monitor, and mitigate safety r

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

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