A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Palantir's Offensive Security team probes our own products, infrastructure, and cloud environment the way a real attacker would. As an Offensive Security Engineer, you will test internal applications and infrastructure, chain findings into realistic attack paths, and work directly with the engineers responsible for the affected systems to get issues closed. A growing part of the team’s work is also developing agentic offensive security tooling: LLM-driven systems that encode operator tradecraft and apply it continuously. You will help in the design of that tooling and prove it out on live assessments. You will also help to coordinate third-party penetration testing engagements, scoping the work with specialized external firms, keeping assessments focused on the risks that matter, and turning their results into concrete remediation.
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The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement guardrails that can withstand real-world load and production use. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will help ensure AI systems are observable, efficient, and dependable in production. Full-stack product shipping: Contribute across the stack when needed because this team ships products, not just models
The worldwide data management software market is massive (IDC forecasts it to be $138 billion by 2026). At MongoDB, we are transforming industries and empowering developers to build amazing apps that people use every day. We are the leading modern data platform and the first database provider to IPO in over 20 years. Join our team and be at the center of innovation and creativity. MongoDB is seeking a Sr. Staff Software Engineer to join the Atlas Core Data Services organization. The organization is responsible for building MongoDB Atlas, our database as a service offering and fastest growing product, along with the API Platform and Developer Tools. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. The Atlas Core Data Services organization builds the software that manages the Atlas cluster infrastructure hosted on the three major cloud providers (AWS, Azure, and GCP), as well as the software that manages the MongoDB database hosted on that infrastructure. We are constantly challenged to design features that ensure Atlas clusters are secure, available, durable, and performant while running large-scale, critical workloads. The Sr. Staff Engineer in this role will drive innovation across the organization and the company, setting technical standards and direction that enable future growth and velocity. We are looking for engineers with the experience and high standards needed to lead at that scale. Our organization champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies systems expertise to build the foundational infrastructure of a popular database, join us. Let's build a faster, more reliable, and highly scalable database platform together. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Responsibilities Define standards and vision for the mission-critical Atlas SaaS data
MongoDB seeks an experienced Software Engineer to help level up IT and launch a new engineering team. This team will work alongside the Internal Engineering department, building enterprise-grade software to enable coworkers to be more effective and efficient. As a Software Engineer, you’ll be contributing to internal tools and platforms, helping design, build, and maintain software that supports critical workflows across the organization. Our ideal candidate Has 2-5 years of professional software engineering experience Experience with a modern programming language (Python, Go, Rust, etc.) Excellent communication skills and a strong desire to solve complex technical problems Comfortable working with modern infrastructure and delivery systems, including containerized applications, Kubernetes, and CI/CD tooling (e.g., Drone.io or similar) Collaborative, detail-oriented, and passionate about developing usable software Bonus Round Experience building full-stack applications, from front-end UIs to backend API handlers to DB migrations Knowledge of any of the following technologies: Next.js, FastAPI, React Position Expectations Build and maintain internal tools and platforms to improve workflows and efficiency Write clean, maintainable code to fix bugs and add new features Collaborate with other engineers and teams to prioritize work and deliver high-impact solutions Success Measures In three months, gain familiarity with internal platforms and workflows, contributing meaningfully to ongoing projects In three months, reduce manual friction for internal processes by delivering functional features or improvements In six months, implement tooling or enhancements that significantly improve internal engineering efficiency and productivity About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with
About the Team The Codex Web Layer team provides the web-based systems and user experiences for Codex across the entire stack, from the Electron-like application framework that powers the application, to the user-facing in-app browser. About the Role In this role, you will be responsible for designing and implementing infrastructure and features end-to-end for the Codex desktop client application. You will help define what it means to be a hybrid agentic/interactive web browser. The team embodies “full stack” development from the lowest-level OS integration to the highest-level interaction design. This role is based in San Francisco. 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: Partner closely with product and design to conceive, design, and build features for Codex web browsing features on macOS and Windows. This role will focus mostly on the backend C++ layer and Chromium, but many features cross the full stack including some TypeScript. Partner with the wider Codex team to deliver a high-performance, stable, and secure application platform for client development. This includes API design and implementation (mostly in C++) and the infrastructure that supports deploying it (in Python, TypeScript, and agentic skills). Work with a small, experienced team of engineers on this critical and rapidly growing product. You might thrive in this role if you: Have significant experience building technically complex features end-to-end. Are a strong C++ developer, especially with experience in browser environments like Chromium and Electron. Since this role is more backend focused, general knowledge of web development and TypeScript is helpful but not required. Thrive in a fast-paced, ambiguous environment. Communicate clearly and concisely across many different roles in the organization. Are self-directed, identifying important work and executing it end-to-end. About OpenAI OpenAI is an AI
About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea
About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G
About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other
About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: The Scheduled Tasks team builds the platform primitives that let applications and agents run work now, later, or for a long time. We own Vercel Workflows, Queues, and Cron: the systems developers use to build long-running, event-driven, and scheduled applications. You will join a team working at the intersection of developer experience and distributed systems. Together, we are building and scaling the products that make it straightforward for developers to coordinate background work, move messages between services, and schedule work with confidence. You will collaborate closely with engineers across Vercel to make these powerful capabilities feel simple, composable, and native to the platform. What You Will Do: Design, build, and operate platform capabilities across Workflows, Queues, and Cron. Help developers build applications and agents that coordinate background, event-driven, and scheduled work. Build APIs, SDKs, and tooling that make it easy to define, run, and manage durable work at scale. Work on the distributed-systems foundations behind scheduling, message delivery, execution, retries, and state. Partner with product, developer experience, and infrastructure teams to turn customer needs into clear, useful developer primitives. Raise the engineering bar through thoughtful design reviews, well-tested code, production ownership, and clear technical communication. Engage with developers and the open-source community to understand where background jobs, queues, and scheduling create friction—and use that feedback to improve th
The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview As a Senior Engineer, Marketing, you'll be embedded with the Marketing team, providing us with technical leadership, consulting, and systems thinking. You'll assemble the orchestration systems, integrations, and AI capabilities that help teams work faster, and in more data‑driven ways. You will lead end‑to‑end design, implementation, and management of the marketing campaign lifecycle system, integrations, internal tools, and learning/experimentation infrastructure. You will report to our Director, Advertising Systems. Responsibilities: You will write high-quality, secure, and well-tested code, contributing to standards and documentation for Marketing infrastructure, data models, and tools You will build the campaign lifecycle orchestration backbone You will build integrations and internal tools that connect project management, collaboration, creative, media, and email/lifecycle platforms You will work with Marketing partners as a technical advisor, translating needs into designs You will integrate AI agents and automations (including LLM-powered flows) into Marketing workflows according to company GenAI guidance You will design and operate data pipelines and models that ingest marketing and performance data into a data layer, supporting experimentation and analytics workflows You will deliver abstractions and APIs that ensure AI systems and our users to create campaign wrap-ups, insights, next-t
Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. The role: As a Senior Software Engineer, Backend, you will leverage your deep technical expertise to ensure alignment, quality, and long-term maintainability across the organization. You will be building strong relationships with cross-functional stakeholders, you will drive project delivery, and ensure our backend infrastructure remains scalable and robust enough to support millions of users worldwide. What you will do Design and develop high-volume, low-latency services and cope with the challenge of working in a distributed environment. Operate mission-critical services at high availability. Collaborate across business units and drive solutions. Explore new solutions and technologies. Build a scalable and reliable system. What you bring in: 5+ years of experience with Scala, Java, or Go Experience of working with scalable, highly available, real-time distributed systems Experience of working with non-relational databases Good understanding of data structures and algorithms Mentoring/ Leadership skills Excellent communication skills in English. Ability to thrive in a dynamic, fast-paced environment. It would be great if you also have
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is entering a period of unprecedented innovation and growth—and there’s never been a more exciting time to join. The Ads Business Engineering team operates at the intersection of engineering, product, sales, and business development, delivering technical expertise and solutions that empower technology partners, agencies, and advertisers to seamlessly integrate with Reddit’s advertising platform. As a key member of this rapidly expanding team, you’ll have the opportunity to take meaningful ownership—driving cutting-edge AdTech integrations, launching and managing strategic partnership programs, and helping scale Reddit’s developer ecosystem. At Reddit, a Business Engineer plays a critical role in driving the success of our advertising API products and platform integrations. This experienced engineer role combines deep technical consulting with hands-on engineering, where you'll guide strategic integrations, often contributing directly to implementation across Reddit’s stack or in the codebases of partners (or direct advertisers). You will be a key technical advisor—trusted to own the end-to-end relationship with Reddit’s most important advertising partners, and execute on the long-term strategy for how we develop an ecosystem of developers. You’ll work across engineering, product, sales, and business development teams to connect Reddit’s capabilities to the evolving needs of the market. You won’t just recommend solutions—you’ll implement them across systems, including platform changes, and also help define framewo
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. Team Description Reddit is poised to rapidly innovate and grow like no other time in its history. We’re currently hiring across three distinct teams: Ad Safety & Verification Team The mission of the Ads Safety & Verification team is to protect the Reddit ads ecosystem so that users have a safe ads experience and legitimate advertisers trust Reddit. This team builds full stack, high scale products that span Reddit’s consumer-facing apps and ads systems. They own integrations with metrics verification and brand safety partners and operate services that scale to reliably handle tens of millions of requests per day. Ads Creative Management (ACM) Team The Ads Creative Management team focuses on the tools and systems advertisers use to create and manage their ad content. From images and videos to headlines and full post creatives, they enable efficient creative management and innovation across the campaign lifecycle. They work closely with AI teams to provide intelligent content suggestions and automation, helping advertisers launch high-quality campaigns faster and more effectively. Brand Innovation Team The Brand Innovation team drives the development of new ad formats that help advertisers maximize reach an
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