Applied Risk Standards Specialist Jobs

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. The opportunity At Synthesia we really care about video generation, especially about human centric avatar video generation. This led us to release models such as EXPRESS-Video , and soon our latest video model - these are the best avatar video models in the world, and we are committed to continuing and double down our efforts in leading that area. Our goal is to get to human centric video models that can generate arbitrary long videos at high resolution with arbitrary actions and events. That means continuously training large generative video models from scratch with the proprietary data pipelines and compute infrastructure to support it at scale. We are looking for a technical leader who owns the full stack end-to-end, someone who bridges pre-training and post-training, sets long-term direction alongside research leadership, and is personally present at the hardest parts of the work. If building foundation model capability from the ground up at a company genuinely committed to leading the field sounds like the right next challenge, this role was written for you. About the role Synthesia's video generation capability is core to everything we ship. It involves roughly 15 people working daily across pre-training a

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Research Engineer in our Video team, you will help build the next generation of production-grade foundation models for human-centric video generation. You will join a highly focused team working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Our mission is to develop and optimize video base models that power realistic, controllable, and emotionally expressive synthetic humans at scale. This is not pure research. This is applied research with direct product impact. You will work on advancing training recipes, scaling distributed systems, improving evaluation frameworks, and optimizing inference to ensure our models are high quality, stable, and efficient enough for real-world deployment. Your work will directly influence models used by tens of thousands of businesses worldwide. What you’ll do You will own and execute end-to-end research and engineering projects, from hypothesis to production impact. This includes: Developing and scaling latent video diffusion models tailored for human-centric video generation Designing conditioning mechanisms to improve control (pose, emotion, script, camera) without sacrificing fidelity Advancing distr

Senior Applied AI/ML Developer (AutoCAD & Civil 3D) — 2 Locations. Apply via Workday.

Senior Applied AI Engineer, Cybersecurity — US, CA, Remote. Apply via Workday.

Lead Applied Researcher — 2 Locations. Apply via Workday.

ML Applied Research Manager — Bucharest. Apply via Workday.

Staff Applied Scientist, 3D - Firefly Foundry — 3 Locations. Apply via Workday.

We built Bubble with a clear mission: to empower everyone to create software. Our AI visual development platform lets anyone, from first-time entrepreneurs to enterprise teams, take an idea from prompt to fully-functional, scalable app across web, iOS, and Android. With over 6 million users in more than 100 countries, Bubble is breaking down the barriers to entrepreneurship and innovation worldwide. Our Product Bubble is the only fully visual AI app builder that lets you vibe code without the code to go beyond prototypes and launch real apps to real users. Chat with AI when you want speed, edit directly when you want control. Bubble's visual editor lets you fine-tune any detail, from the design to privacy rules and programming logic, so you're never stuck, even if AI hits its limits. Everything you need comes built in: a unified web and native mobile editor, enterprise-grade hosting, security, database management, and automatic scaling that grows with your business. You can build just about anything on Bubble, and our community is living proof. Mailead grew a $10K investment into a $2M valuation, and Faceless.video went from zero to $1M+ ARR in under a year. People aren't just launching products on Bubble, they're building real businesses. See how Bubble builders are shipping apps that change industries, solve problems, and shape the future here: Inspiring builders, breakthrough apps . Why Join Bubble Now? The rise of AI-generated software has validated everything Bubble has been building toward for over a decade. But pure AI-generated code is fragile, hard to debug, and rarely production-ready. Bubble bridges that gap, combining the speed of AI with a structured visual platform that produces stable, scalable, secure software. The people who join Bubble right now will help define what that means for millions of builders around the world. If you've ever wanted to work on something that genuinely changes who gets to build, this is your moment. About the Team: We’re ex

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record. We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all. The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you. At Datadog, we place value in our office culture: the relationships and collaboration it builds, and the creativity it bring

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on

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. This is a hybrid role. It requires going to the local office 3 times a week. The Auth0Lab Team We are a small team of engineers exploring new Auth0 products and features ideas. We take things from 0 to 1 and we look to shape the future of identity. Our team has had a big role shaping the identity industry: we were all early at Auth0, which shaped how devs do authentication as part of Auth0Lab we incubated Auth0 FGA which redefined how authorization is done across the industry and we also incubated Auth0 for AI agents which defined auth for AI agents We are currently focused on enabling builders and companies of any size to ship production grade AI agents, by helping them with identity and security. We believe data, and developing our own models will play a huge role in this. The role We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation. You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you. This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal. We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to ha

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. This is a hybrid role. It requires going to the local office 3 times a week. The Auth0Lab Team We are a small team of engineers exploring new Auth0 products and features ideas. We take things from 0 to 1 and we look to shape the future of identity. Our team has had a big role shaping the identity industry: we were all early at Auth0, which shaped how devs do authentication as part of Auth0Lab we incubated Auth0 FGA which redefined how authorization is done across the industry and we also incubated Auth0 for AI agents which defined auth for AI agents We are currently focused on enabling builders and companies of any size to ship production grade AI agents, by helping them with identity and security. We believe data, and developing our own models will play a huge role in this. The role We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation. You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you. This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal. We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to ha

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We’re looking for applied scientists with a Machine Learning and Artificial Intelligence background to build AI technologies and make Figma products more magical.. You will be driving fundamental and applied research in this area. You will be combining industry best practices and a first-principles approach to design and build AI/ML models and systems to improve Figma’s products. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: You will be driving fundamental and applied research in AI. You will explore the boundaries of what is possible with the current technology set to build best in class models for Figma’s domains You will be combining industry best practices and a first-principles approach to build cutting edge Generative AI models, using techniques like Supervised Finetuning (SFT), Reinforcement Learning (RL), prompt improvements and synthetic data generation Work in concert with product and infrastructure engineers to improve Figma’s products through AI powered features Collaborate closely with product managers and engineers to transform user feedback into requirements for AI systems Build evaluation systems to measure and improve quality of AI features in Figma products We'd love to hear from you if you have: Extensive experience in building generative AI features through prompt engineering, and fine tuning models in production environments Experience working on deep learning and generative AI frameworks li