Staff Ai Engineering Jobs

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our Stockholm office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

At Secureframe , we are not just a company; we are at the forefront of revolutionizing cybersecurity compliance. Recognized as one of the industry's most innovative and trusted providers, Secureframe has consistently received accolades for our advanced technology solutions and commitment to excellence. With a robust portfolio of products that safeguard thousands of businesses worldwide, we have been featured in major publications such as Forbes’ next billion dollar startups , TechCrunch, and The Wall Street Journal for our transformative impact on the way companies achieve and maintain compliance standards. As we continue to grow, our mission remains clear: to provide seamless, secure solutions that enable businesses to focus on what they do best. Joining Secureframe means becoming part of a team dedicated to professional excellence and continuous learning in an environment that values creativity and forward-thinking. Secureframe is backed by top VCs including Kleiner Perkins, Accomplice, Gradient Ventures (Google’s AI Fund), BoxGroup, Village Global, and many more. Join Secureframe's Engineering team and help shape the future of compliance automation. Secureframe highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a defined radius of a Secureframe office), Secureframe considers working in the office, approximately 30% of the time under current policy, to be an essential function of the employee's role. Benefits Medical, dental, and vision benefits for you and your dependent(s) Flexible PTO 401(k) Paid family leave Ground floor opportunity as an early member of the team What you'll do ... Lead technical scoping, design, and implementation of new end-to-end functionality Perform detailed code reviews and provide technical mentorship to engineers Lead architecture and architectural discussions for core parts of the Secureframe application Own multi-team c

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 Workforce Identity Cloud Security Engineering group is looking for an experienced and passionate Staff Site Reliability Engineer to join a team focused on designing and developing Security solutions to harden our cloud infrastructure. We embrace innovation and pave the way to transform bright ideas into excellent security solutions that help run large-scale, critical infrastructure. We encourage you to prescribe defense-in-depth measures, industry security standards and enforce the principle of least privilege to help take our Security posture to the next level. Our Infrastructure Security team has a niche skill-set that balances Security domain expertise with the ability to design, implement, rollout infrastructure across multiple cloud environments without adding friction to product functionality or performance. We are responsible for the ever-growing need to improve our customer safety and privacy by providing security services that are coupled with the core Okta product. This is a high-impact role in a security-centric, fast-paced organization that is poised for massive growth and success. You will act as a liaison between the Security org and the Engineering org to build technical leverage and influence the security roadmap. You will focus on engineering security aspects of the systems used across our services. Join us and be part of a company that is about to change the cloud computing landscape forever. As a Staff Engineer, you should be able

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 Workforce Identity Cloud Security Engineering group is looking for an experienced and passionate software security engineer to join a team focused on designing and developing Security solutions to harden our frameworks & infrastructure. We embrace innovation and pave the way to transform bright ideas into excellent security software solutions that help run large-scale, mission-critical software. We encourage you to prescribe defense-in-depth measures, industry security standards, enforce the principle of least privilege to help take our Security posture to the next level. Our Security engineering team has a niche skill-set that combines Security domain expertise with the ability to design, implement and rollout security features and functionalities without adding friction to product functionality or performance. We are responsible for the ever-growing need to improve our customer safety and privacy by providing security services that are coupled with the core Okta product. This is a high-impact role in a security-centric, fast-paced organization that is poised for massive growth and success. You will act as a liaison between the Security org and the engineering org to build technical leverage and influence the security roadmap and direction. You will focus on engineering security and privacy aspects of the systems used across our services while working on a weekly release cadence. You will be empowered to propose stimulating new

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: AI and ML are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing, we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Core ML team is responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting Generative AI technologies to enable an intelligent, scalable, and exceptional service experience. The team develops and enhances AI models, ML services, and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning, and guardrails for a wide range of applications at Airbnb. The richness of Airbnb's data, the complexity of its marketplace, and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to long-term innovation to solve complex problems, and to do that we need experienced ML ​​The Difference You Will Make: In this Senior Staff role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products (e.g., assistive agents, issue resolution, and tooling). Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently. You will partner closely with product, engineering, design, operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes. A Typical Day: Define evaluation strategy and suc

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The CS AI product team is responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning, alignment and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The Difference You Will Make: As a senior staff machine learning engineer, you will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on Airbnb’s ML Infrastructure. You will partner with product managers, software engineers, data scientists and operation teams to brainstorm, design and develop AI products such as AI Assistant, Autonomous agent, recommendation, travel planning, and many more products that make meaningful impacts in the world of travel. A Typical Day: Work with large scale structured and unstructured data; explore, experiment, build and continuously improve foundation models for Airbnb product, business and operational use cases. Create a multi-year tech roadmap that enables our team to stay on the leading edge of the rapidly evolving AI landscape and

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role This is where security meets innovation at enterprise scale. As a staff security engineer, applications at WRITER, you'll be building the security foundations that protect the AI systems powering some of the world's most recognizable brands. You'll work at the intersection of application security, AI infrastructure, and developer enablement—partnering with engineering teams to embed security into every line of code while ensuring our platform remains both powerful and trustworthy. The opportunity is massive: you'll help define how enterprise AI applications are secured, from threat modeling our LLM architectures to building automated security controls that scale across our growing platform. This isn't about saying "no"—it's about finding creative ways to say "yes, and here's how we do it securely." You'll tackle challenges that most security engineers never encounter: securing AI agents, protecting training data pipelines, and designing controls for systems tha

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

Staff Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI-powered innovations to enhance search relevance and ITSM workflows. What You Will Do Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customer’s data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries. Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 5+ years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals wh

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role The Portfolio Services team is at the core processing Addepar’s client data. We play a pivotal role in enabling data to flow across our data platforms into our client’s instances. Working at the critical intersection of application, analyst, and operations teams, we promote developer velocity and robust process automation. Working with a healthy mix of new technologies and existing core applications, the team thrives on solving complex challenges to deliver high-impact solutions. If you're passionate about creating true engineering leverage, this is the team for you. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What You’ll Do Work with teams across the organisation to: Develop resilient distributed services and high quality tooling to support product operations and engineering. Investigate and debug complex issues that span across teams and applications. Drive software delivery and improve the engineering processes we use to develop and release software. Who You Are Comfortable working independently, with a bias for action. Thrives in ambiguous spaces where there isn’t a clear solution. Enjoys digging into n