Data Intelligence Systems Engineer Jobs

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. Are you ready to join a dynamic team committed to advancing technology? At Micron, we value collaboration and innovation to deliver flawless results. As an Engineer on our Automation Development team in Taichung, Taiwan, you will have a meaningful role in supporting engineering efforts and leading continuous improvement projects involving manufacturing tools, materials, and processes. This opportunity allows you to contribute to high-density advanced memory production while working with passionate professionals in an encouraging environment. Responsibilities and Tasks Support Statistical Process Control (SPC), Advanced Process Control (APC/Run-to-Run), Fault Detection and Classification (FDC), and Data Intelligence (DI) applications. Deploy, monitor, and continuously improve AI-Enabled and data-driven manufacturing solutions. Apply Artificial Intelligence and Generative AI tools to improve operational efficiency, troubleshooting effectiveness, and engineering efficiency. Collaborate with cross-functional teams to investigate process deviations, analyze manufacturing data, and drive yield and efficiency improvements. Requirements Proficient in English. Bachelor's degree or equivalent experience in Engineering, Computer Science, Information Technology, Automation, Industrial Engineering, or related fields. Familiarity with manufacturing systems, data analysis, programming, or Artificial Intelligence applications is valued.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About the Team The Finance Platform & Technology team builds and scales the systems and data architecture that power OpenAI’s core financial operations. We enable business agility, compliance, and operational excellence across procure-to-pay, quote-to-cash, supply chain, financial planning, and asset management. We partner with Procurement, Accounting, Tax, Legal, Security, Data, and Engineering to modernize workflows through thoughtful platform design, reliable integrations, scalable automation, and trusted data. About the Role As a Business Systems Lead for Procure-to-Pay, you will be a hands-on engineer who designs, builds, and operates the integrations and first-party applications that power OpenAI’s procurement workflows. You will translate business needs into secure, scalable software, APIs, data flows, and automation across Oracle Fusion, Zip, and connected platforms. You will build the future of buying at OpenAI using OpenAI’s own technology, from guided intake and approval experiences to supplier onboarding, purchasing, receiving, invoicing, and downstream financial data flows. You will own the technical roadmap and support model for these capabilities, improving today’s platforms while deciding where to integrate, configure, or build as OpenAI scales. Your core strength will be software and integration engineering. You will personally write code, troubleshoot cross-system failures, and take solutions through testing, deployment, and production support. You will also make targeted functional configurations in procurement platforms and partner with functional specialists on deeper process and module design. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and operate integrations across Oracle Fusion, Zip, and connected systems using APIs, events, messaging, and batch interfaces where appropriate. Build first-party

NVIDIA's invention of the GPU transformed computer graphics, parallel computing, and modern AI. Today, NVIDIA high-performance processing platforms power breakthroughs across generative AI, autonomous systems, scientific computing, robotics, and high-performance data centers. NVIDIA's compiler technologies are key enablers of AI at scale, turning rapidly evolving deep learning models into highly optimized GPU programs for training and inference. As AI models, GPU architectures, and compiler systems become more sophisticated, AI compiler quality has become a deep technical challenge at the intersection of compilers, machine learning frameworks, numerical computing, formal reasoning, and large-scale systems engineering. To address these complex challenges, we are seeking an Engineering Manager to spearhead our strategy for verifying AI compilers built for next-generation deep learning workloads. This is a hands-on compiler engineering leadership role for someone who understands where compiler quality can regress in modern AI compiler stacks. What You'll Be Doing: Lead, mentor, and grow a highly technical team responsible for AI compiler verification. Own the verification of next-generation AI workloads, including LLMs and agentic AI systems, across the full spectrum of the AI compiler stack and execution pipeline. Define formal-verification requirements for AI compiler transformations and generated GPU programs, including formal specifications, tensor/operator semantics, semantic preservation, code equivalence, numerical behavior, and properties stressed by AI-generated or adversarial workloads. Drive the use of AI-assisted and compiler-aware verification techniques, including adversarial workload generation, differential testing, symbolic reasoning, formal methods, fuzzing, static analysis, and automated debugging. Partner closely with AI compiler

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. Job Summary As a Process Control Systems Engineer, you will integrate and monitor key performance indicators across semiconductor manufacturing Defense Line systems, including SPC, FDC, R2R, and other process control applications. You will identify KPI gaps, coordinate CAPA follow-up, track actions through closure, and provide management-level performance visibility. You will also develop dashboards, retrieve and analyze data using SQL and Snowflake, support data digitalization, and participate in AI-enabled manufacturing and analytics projects. This role requires strong analytical thinking, cross-functional coordination, learning agility, and an interest in semiconductor process control and smart manufacturing. Key Responsibilities Integrate and monitor KPIs across different Defense Line and PCS systems. Identify performance gaps and follow up on corrective and preventive actions. Track action owners, due dates, risks, effectiveness verification, and closure status. Develop dashboards for KPI, system health, issue, and CAPA monitoring. Retrieve, clean, transform, and analyze data using SQL and Snowflake. Support AI, machine learning, and advanced analytics applications. Coordinate with process, manufacturing, quality, automation, IT, and global PCS teams. Participate in PCS integration, digitalization, and management-assigned projects. Maintain technical documents, governance workflows, and audit evidence. Qualificati

We are looking for a talented Senior System Software Engineer to help build NVIDIA Halos, our full-stack safety critical platform for physical AI: autonomous vehicles, humanoids, industrial robots, and intelligent machines that sense, decide, and act in the real world. This role is equally grounded in ISO 26262 functional safety engineering and embedded systems, rich operating systems, virtualization, accelerated computing. If you have a good understanding of System Software development on Real Time OS (RTOS), ARM architecture, Virtualization, and experience with ISO 26262 safety lifecycle, we want to hear from you! We are a leading artificial intelligence computing company and are paving the way with innovations in gaming, visualization, supercomputing, and autonomous vehicle and robotics safety platforms. NVIDIA gives automakers, tier-1 suppliers, automotive research institutions, and startups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for autonomous vehicles. Our unified computing architecture makes it possible to train deep neural networks in the data center on the NVIDIA DGX™, and then seamlessly run them on NVIDIA's Halos platform inside the vehicle. Leading vehicle manufacturers, tier 1 suppliers, mapping and simulation companies, software and sensor providers, and startups around the world are developing on the NVIDIA Halos® platform to deliver the best solutions for the new world of mobility. As a System Software Engineer, you will get an opportunity to work on high-performance NVIDIA edge AI platforms running complex mixed-criticality software stacks across QNX, Linux, hypervisors, safety partitions, accelerators, and real-time AI workloads, and work alongside industry experts in diverse teams and projects. <

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. Senior Software Engineer, Security Engineering We are looking for a Senior Software Engineer that will join the Auth0 Security Engineering organization. In this role, you will join a team of Software Engineers dedicated to building and managing services that secure the platform that Auth0 runs on. You will be instrumental in expanding our platform security controls and architecting custom workflows in a scalable, reliable manner. What You Will Do Service Development: Build, maintain, and operate platform security services and controls using Python, Node.js, or Golang. Security Data Pipelines: Design, build, and optimize custom workflows to ingest, process, and distribute security data to downstream systems at scale. Scalable System Architecture: Architect maintainable, secure, and resilient microservices and platform integrations that protect our infrastructure without adding friction for engineering teams. Engineering Quality: Write clean, testable, and well-documented code while driving technical designs and participating in code reviews to maintain high engineering standards. What You Bring Software Development Experience: 5+ years of hands-on experience designing, building, and maintaining production-grade software services. Core Language Proficiency: Hands-on mastery of Python, Node.js, or Golang. System Design Expertise: Strong track record of designing scalable, maintainable, and secure software architectures. Cloud & Containers: Solid expe

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle’s overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle’s world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall CAS is parallel and complementary to our Main Artificial Intelligence (AI) autonomy stack, and has a close relationship with our vehicle hardware and safety teams in order to architect redundancy into our overall driving system. The CAS Verification & Validation (CAS V&V) is a multidisciplinary team data, software and systems engineers defining and building metrics to measure the Collision Avoidance System performance and work with the Systems Design and Mission Assurance (SDMA) and QA teams to develop validation plans for the features. In this role, you will: Apply distributed computing algorithms to analyze petabytes of urban driving data. Develop metrics and tools to analyze errors and system improvements. Work closely with CAS engineers to evaluate system performance. Collaborate with Perception engineers to define metrics for autonomous driving. Partner with Planning engineers to measure performance in complex urban environments. Qualifications: BS, MS, or PhD degree in computer science or a related field Fluency in C++ and/or Python Extensive experience with programming and algorithm design Bonus Qualifications: Experience with analysis of latency for safety-critical software systems Experience with petabyte-scale distributed computing (Spark, Databricks, generic MapReduce pipelines) <li

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 Technology, Data & Intelligence Team Okta’s Technology, Data & Intelligence (TDI) team delivers the systems, tools, and services that power internal operations across the company. From core infrastructure to enterprise platforms, we partner across functions to drive scale, reliability, and innovation through technology. The Staff Site Reliability Engineer Opportunity Okta Federal, Inc. is looking for an experienced Staff TDI Site Reliability Engineer to help build, improve, and maintain our cloud platform services that help Okta support the most sensitive national security missions. The Site Reliability Engineering team delivers foundational infrastructure capabilities that enable corporate engineering teams to operate securely, reliably, and at scale. You’ll play a key role in designing and implementing complex cloud-based engineering enablement systems, while ensuring compliance with strict government requirements. What you’ll be doing Operate and maintain enterprise grade solutions within air-gapped environments. Build, run, and monitor development tools, pipelines, and infrastructure with a security-first mindset. Operate autonomously within secure facilities. Maintain SLOs/SLIs for workloads with no dependency on external monitoring or SaaS tooling. Own runbooks and incident response procedures tailored to limited external escalation paths. Participate in POA&M remediation and support annual/recurring Authority to Oper

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. Okta’s Technology, Data & Intelligence (TDI) team delivers the systems, tools, and services that power internal operations across the company. From core infrastructure to enterprise platforms, we partner across functions to drive scale, reliability, and innovation through technology. The Staff Site Reliability Engineer Opportunity Okta Federal, Inc. is looking for an experienced Staff TDI Site Reliability Engineer to help build, improve, and maintain our cloud platform services that help Okta support the most sensitive national security missions. The Site Reliability Engineering team delivers foundational infrastructure capabilities that enable corporate engineering teams to operate securely, reliably, and at scale. You’ll play a key role in designing and implementing complex cloud-based engineering enablement systems, while ensuring compliance with strict government requirements. What you’ll be doing Operate and maintain enterprise grade solutions within air-gapped environments. Build, run, and monitor development tools, pipelines, and infrastructure with a security-first mindset. Operate autonomously within secure facilities. Maintain SLOs/SLIs for workloads with no dependency on external monitoring or SaaS tooling. Own runbooks and incident response procedures tailored to limited external escalation paths. Participate in POA&M remediation and support annual/recurring Authority to Operate activities. Support and run mission criti

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent breakthroughs in multimodal AI have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering. We're building the systems and experiences that turn these research advances into products used daily by creators, professionals, businesses, and consumers around the world. Our team sits at the intersection of research, product, design, and infrastructure. We work closely with model researchers, mobile engineers, frontend engineers, and platform teams to build intuitive experiences and scalable systems that power image generation at global scale. Whether users are creating marketing assets, visualizing ideas, editing photos, designing products, or simply exploring their creativity, our goal is to make visual creation feel as natural as having a conversation. About the Role We are looking for an experienced Full Stack Engineer to join the Image Generation team and help shape the future of AI-powered visual creation. In this role, you'll own features end-to-end across both frontend and backend systems, building the experiences that enable users to generate, edit, organize, and interact with images inside ChatGPT. You'll work across the entire stack—from highly interactive user interfaces and real-time workflows to backend services, APIs, orchestration systems, and data infrastructure. This role is ideal for engineers who enjoy moving fluidly between product development and systems engineering, collaborating closely with design, product, and research teams to rapidly bring new AI capabilities to users. You'll help define entirely new interaction paradigms as multimodal AI continues to evolve. In

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. Position Overview: We are seeking a highly technical Staff Observability Site Reliability Engineer with a specialty in Splunk to own and evolve our Splunk ecosystem. In this role, you will move beyond simple monitoring to delivering a world class, comprehensive, scalable Observability Platform that enables our SRE teams and business partners. You will treat infrastructure as code —utilizing Terraform and strong coding proficiency in Go, Python, or Ruby —to automate the deployment of agents and collectors across complex distributed systems. Key Responsibilities Automated Infrastructure: Design, build, and maintain scalable observability infrastructure using tools like Terraform. Splunk Engineering: Optimize the collection, processing, and storage of log data to ensure high reliability and low latency of our Splunk services Incident Response: Participate in on-call rotations and lead post-incident reviews to drive systemic improvements and "observability-driven development." Automation: Eliminate "toil" by automating the deployment and scaling of observability agents and collectors. Required Skills & Experience (The Essentials) Log Management: Minimum 5+ Experience scaling and managing Splunk Cloud at scale (1000+ SVCs), including Workload Management (WLM) and HEC optimization. Visualization: Expertise in creating intuitive, actionable Splunk dashboards that correlate data across multiple sources. SRE Mindset: Minimum 5+ years of experience in an SRE, Dev