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Software Development Engineer Iii Data Jobs

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2 days ago

About the Team The Intelligence & Investigations Engineering team builds systems that detect, analyze, and disrupt abuse across OpenAI’s products. We partner closely with the Child Safety team and cross-functional groups to protect users while advancing OpenAI’s goal of developing AI that benefits everyone. About the Role As a Fullstack Engineer focused on child safety, you’ll build data-intensive, AI-powered applications and infrastructure that enable operators and investigators to work effectively and responsibly. You’ll adapt quickly in ambiguous, fast-moving environments to deliver well-crafted, reliable tooling for high-severity safety work. *Candidates should understand this role involves exposure to sensitive and egregious content. In this role, you will: 7+ years of experience as a software engineer Prototype, build, and maintain intelligence systems that detect, triage, and enable efficient human review of possible high severity harm Work hand in hand with operators and investigators, designing and delivering systems that enable them to do their work faster, more accurately, and more safely. Develop across the stack: UIs, services, pipelines, and anything else required to solve the problems we face. Interact with partners across Product Policy, Platform Integrity, Safety Systems, and Research Contribute to the team’s technical strategy, especially for child safety related tools and systems Report on impact in a data-driven fashion You might thrive in this role if you: Have a strong software engineering foundation and enjoy owning systems end-to-end—from infrastructure and data ingestion to frontend tooling Are energized by working at the frontier of AI capabilities, integrating new models and APIs into practical systems Have experience building and operating large-scale data pipelines or search/retrieval systems Are proficient in Python and/or TypeScript, and familiar with tools like Spark, Kafka, Flink, data warehouses, and SQL Take a product-minded ap

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2 days ago

About the Role The Enterprise Trust & Governance team builds the control plane that lets the world’s largest organizations deploy Perplexity broadly and with confidence. Computer and our agents work across a growing share of our customers’ environments, tools, and models. For administrators, that makes precise, enforceable control essential: who can do what, with which data, through which agents, and within what usage limits. This team makes those controls easy to manage, reliable and consistent across every product, and transparent to the people accountable for them. This is a product and platform engineering role with end-to-end ownership, from shaping the architecture and policy models to shipping the experiences our customers’ administrators and security teams use every day. You’ll work across product and infrastructure teams to turn complex enterprise requirements into reusable primitives and intuitive controls. The scope spans identity and provisioning, fine-grained role-based access across connectors, tool actions, and models, customer-managed encryption keys, admin APIs, audit logs, and policy and usage controls. Strong governance helps enterprises move from pilots to company-wide rollouts and gives them the confidence to entrust agents with greater responsibility over time. Key Responsibilities Own enterprise identity and provisioning, including SSO (SAML/OIDC), SCIM, WorkOS integrations, and support for identity providers such as Okta and Microsoft Entra ID. Build the permissions platform, with fine-grained roles and permissions for connectors, tool actions, models, and model effort levels, enforced consistently across products and agent workflows. Design and ship secure, well-documented admin APIs for audit logs, members, groups, roles, and settings. Build policy controls for model and feature availability, staged rollouts, model deprecations, usage and spend limits, alerts, and cost-center allocation. Build admin-facing analytics for adoption, usage,

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Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Engineering Manager - Software Engineering Engineering Manager – Software Engineering Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realise their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview The Mastercard Payment Networks team is looking for an Engineering Manager to lead high-performing teams building scalable and reliable backend systems. As an Engineering Manager, you will be responsible for driving technical delivery, ensuring engineering excellence, and building strong teams delivering complex distributed systems. This role requires a balance of technical depth, ownership, and strong execution focus. You will lead teams working on systems that handle high-volume transaction data, provide secure and efficient a

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3 days ago

We are looking for a Sr. Engineer to design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. You will work at the intersection of distributed systems, developer platforms, and agentic AI — building the foundational services that enable teams across the company to develop, deploy, orchestrate, and operate autonomous AI agents at production scale. What you will be doing: Build and develop platform services that manage the full agent lifecycle from registration through deployment, execution, and teardown Architect multi-tenant Kubernetes execution environments with pod lifecycle management, per-tenant namespace isolation, persistent storage, admission policy enforcement, and identity propagation Develop and maintain automated CI/CD pipelines using GitLab CI and ArgoCD, including reusable pipeline templates and deployment blueprints that standardize how agents are built across teams Build framework-agnostic infrastructure supporting multiple agent SDKs and harnesses — lifecycle hooks, skills configuration, memory services, and OTEL instrumentation — so teams can onboard new agent frameworks without platform changes Build and operate Kafka-based message pipelines and real-time event streaming using Redis PubSub and SSE Develop data ingestion pipelines, access interfaces, and storage layers that power AI agent knowledge and context Implement session management for state persistence, conversation history, and agent recovery across sessions Develop multi-layer auth using OAuth 2.0, JWT validation, token exchange, and gateway integration, and manage secrets lifecycle with Vault (provisioning, rotation, container injection) Partner with security teams on compliance, access controls, and approval workflows for agent operations What we need to see: Bachelor's or Master's degree in Computer Science, Engineering, or

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N
3 days ago

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is searching for a creative, highly motivated and independent engineer with expertise in system software with security background to join the SOC System Software organization. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting SOC based product lines ranging from autonomous vehicles, robotics, consumer graphics, and edge AI. What You’ll Be Doing: Lead all HDCP (High-bandwidth Digital Content Protection) activities across SoC-based projects, leading the feature roadmap, protocol implementation, compliance certification, and delivery across chips, platforms, and products. Develop and maintain secure-engine firmware on a RISC-V based secure processor. Deliver end to end HDCP solution across multiple software stacks spanning Linux, Android for automotive, and consumer platforms. Drive firmware production signing readiness, rollback-prevention strategies, and key-provisioning workflows. Serve as the security primary contact for the team, leading all aspects of threat modeling, static analysis, vulnerability tracking and remediation, and security compliance across all projects. Collaborate with multi-functional teams spanning HW design, boo

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Nvidia
📍 Santa Clara, United States
3 days ago

As a Robotics Software Engineer on the Isaac Applications Team, you will bring together the software and hardware that enable Physical AI robots to operate in the real world. You will build working robotic systems and end-to-end workflows for engineers and AI agents. These workflows connect data, simulation, and real-world deployment to continuously expand and improve robot capabilities. We’re looking for strong software engineering skills, broad robotics knowledge, and enthusiasm for working hands-on with physical robots when taking ideas into practice. You enjoy understanding how components interact, solving problems across their boundaries, and seeing them come together to deliver new robot capabilities. What you will be doing: Lead the forefront of Physical AI progress in both simulated and real humanoid robots by building the humanoid reference platform that features NVIDIA's robotics technologies. Build end-to-end workflows to develop, evaluate, and deploy increasingly autonomous and interactive robot capabilities. Extend our platform to new robot embodiments and demonstrate its adaptability through hands-on integration and validation. Address real-world compute, latency, and bandwidth constraints on physical hardware. Collaborate across teams in Shanghai, America, and Europe to connect capabilities and deliver reliable robotic systems. What we need to see: Master’s degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience). 8+ years of relevant industry experience working on robotics software. Hands-on experience integrating, deploying, and testing software on physical robots, and confidence working directly with hardware when needed. Experience deploying and evaluating learned policies to control physical robots. Broad working knowledge of robotics software, hardware, AI, an

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3 days ago

NVIDIA DGXC Storage team handles some of the fastest training and inference tasks. Every GPU cycle depends on a storage platform built to keep tens of thousands of accelerators continuously busy. It maintains exabytes of data securely and powers the largest AI workloads worldwide across cloud, neocloud, and on-prem setups. With the growth of accelerated computing, storage is essential. It can make the difference between effective GPU use and wasted potential, and between launching a frontier model on time or missing the deadline by months. We’re looking for a hands-on Storage Software Engineer to join the storage team as an individual contributor and technical lead. You will contribute to open-source parallel and distributed file systems and keep our largest GPU clusters fast, reliable, and durable. You will stay deeply hands-on: writing and reviewing production code, chasing root causes in the field, and setting the configuration and tuning standards our GPU fleets run on. This is a chance to do foundational storage engineering for the AI era at the company that introduced accelerated computing. What you’ll be doing: Contribute to open-source file systems. Contribute code to open-source parallel and distributed file systems, and distributed object storage. Upstream fixes and features, and engage directly with the upstream communities and maintainers. Serve as a hands-on storage software lead. Write and review production code yourself, and read kernel, NFS, NVMe-oF, or SPDK source when a bug requires it. Make the final technical calls on storage deliveries against measurable targets. Triage and troubleshoot at scale. Triage, troubleshoot, and root-cause large, complex storage issues across very large GPU clusters (tens of thousands of GPUs) — I/O and metadata performance, data corruption, and recovery. Validate architecture and capabilities. Validate storage architecture, capabilities, performance, and durabil

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N
3 days ago

NVIDIA’s invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement. NVIDIA data center systems have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. These platforms bring together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA Networking, NVIDIA Data Center CPUs, and a fully optimized NVIDIA AI and HPC software stack. We are seeking an excellent Senior System Engineer to work on bring up, integration, validation and troubleshooting for compute tray platforms of GPU Racks — ensuring servers are fully functional and validated as per requirement before mass deployment in data centers. What you’ll be doing: Working with a global team of architects and developers on NVIDIA AI server system (CPU, GPU, Memory, NIC, PCIe, NVMe SSD, Cooling, etc.) designs. Working closely with hardware teams to influence hardware system design, reviewing schematics and board design to ensure speed of light execution. Using simulation and emulation to left-shift early design and initiate new concepts and innovations. Hands on debug and support of early server prototypes bring-up and power on test debug in datacenter system labs. Factory and Manufacturing support: Support manufacturing flows, firmware updates, and diagnostic procedures. Ensure BOM change signoff and proc

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N
3 days ago

NVIDIA is seeking a Senior Software Engineer to help us develop distributed storage services for AI/ML. In this role you will work closely with the broader NVIDIA team to design and build a reliable, scalable, and efficient storage-as-a-service tailored to AI applications that can be deployed anywhere and scale without limitations. This service supports the whole NVIDIA critical business from graphics drivers to autonomous vehicles to deep learning frameworks. To achieve this goal, we are looking for an engineer with a deep understanding of distributed systems, outstanding design skills, and a track record in building and delivering large-scale distributed services. What you will be doing: Leading the overall architecture and design of our distributed storage service optimized for AI/ML Develop and maintain distributed, robust and scalable Go programs deployed to state of the art open-source ecosystems, including Kubernetes. Develop and maintain user-space applications, containers, Go-bindings, and CLI tools. Building features for a distributed storage service to enhance availability and reliability for large-scale deployments Engaging and collaborating with NVIDIA Research, Computing, Product teams, cross-functional teams, and external customers to deliver Cloud services. Automating distributed storage service end-to-end, including deployment, management, and monitoring What we need to see: Bachelor’s of Science in Computer Science, or related field (or equivalent experience) with 8+ years of industry experience Strong background in developing distributed systems involving Golang, Kubernetes, and Cloud Service Provider integrations Strong track record of delivering distributed services in a variety of distributed computing environments Experience in i

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Cohere
📍 Canada• Full-time• Remote• $205K – $315K/yr
3 days ago

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? This role is for a highly experienced Back-End Software Engineer who wants to work on core systems that shape how the platform (Model Vault) operates. You will help define the architecture of the platform where reliability, security, performance, and simplicity all matter, and where many of the problems do not have off-the-shelf solutions. Model Vault is Cohere’s inference platform for deploying and operating models securely at enterprise scale. The team owns the systems between a customer and the underlying AI infrastructure, including identity, deployments, metering, billing, security, privacy, and confidential computing. We are strengthening these systems as Model Vault grows, with the goal of scaling to millions of users and supporting some of the world’s most demanding enterprise workloads. As a Senior/Staff Software Engineer, you will: Evolve and scale the backend systems that power Model Vault, including authentication and authorization, deployment management, billing, metering, and customer lifecycle. Lead major architectural initiatives across identity, payments, usage systems, platform scalability, and o

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