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Lead Machine Learning Scientist Jobs

10,000 active opportunities · Updated for October 2026

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Explore current lead machine learning scientist jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Pinterest
📍 San Francisco• $314.6K – $550.5K/yr
21 days ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a strategic and experienced engineering leader to define the technical direction for Pinterest’s advertiser measurement and signal-quality ecosystem. In this role, you’ll lead managers and senior technical leaders across Interfaces, Ingestion, User Match, and Conversion Quality, driving multi-year investments in machine learning, data platforms, experimentation, privacy, and production reliability. You’ll partner closely with Product, Data Science, Ads Quality, Infrastructure, Privacy, Legal and Sales to translate complex advertiser and business challenges into scalable solutions—and build an inclusive, high-performing organization equipped to deliver measurable impact at scale. What you’ll do: Define technical strategy and investment priorities across Interfaces, Ingestion, User Match, and Conversion Quality. Lead

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OpenAI
📍 Seattle• Full-time• Remote• $437K – $485K/yr
27 days ago

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. We are evolving experimentation systems to help teams learn from product behavior and make better evidence-based decisions. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are looking for a Machine Learning Engineer to lead the technical direction for ML-powered experimentation and insights capabilities. You

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Ramp
📍 New York• Full-time• Remote• $200K – $330K/yr
28 days ago

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis. What You’ll Do Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud Partner closely with Fraud Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in

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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! At Figma we believe design doesn’t end in a file or with your designer - it includes everything that goes into the product you ship: the production code that ties it all together, the systems and developer tools that make that code reliable, the context you provide to our AI agents, and the documentation that keeps everyone on the same page. The Roundtripping Area at Figma is redefining how Designers, PMs and Engineers collaborate. We are responsible for agentic workflows enabling ideation and prototyping on production codebases as well as accelerating the journey from design to code. In 2023, we launched Dev Mode, a suite of features that give developers everything they need to navigate design files and transform designs into code. In 2025, we introduced Figma’s MCP, accelerating how ideas get to production. Looking to the future, we aim to further reduce the barriers between design to code and code to design allowing ideation, prototyping and productionalising to happen seamlessly where it most makes sense. Our Roundtripping team is expanding, and we’re hiring AI Product Engineers across multiple levels in the UK. We’re looking for people who have built generative AI products and are eager to lead AI efforts end-to-end, from early ideas to production. Join us in shaping the future of AI at Figma. What you’ll do at Figma: Build and evolve Dev Mode our MCP tools and Make, Figma’s leading tools for dev/design collaboration Take part in building new 0→1 products within the agentic coding space Col

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Engineering Manager, Machine Learning Credit Risk Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies from the world’s largest enterprises to the most ambitious startups use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Credit Risk team develops intelligent systems that help Stripe identify high-risk accounts, minimize credit losses, and improve profitability. Credit risk is a complex machine learning problem that requires us to distinguish emerging risk from healthy business activity while giving legitimate users a clear and reliable experience. Our team consists of machine learning engineers who build models and systems used across Stripe’s credit-risk products. We work closely with partners in Product, Data Science, Credit Strategy, Operations, and other engineering teams. Together, we help stakeholders make informed decisions and support sustainable growth wherever credit risk affects Stripe’s products. What you’ll do We’re looking for an engineering manager to lead the Credit Risk team and shape how Stripe uses machine learning to manage credit risk at scale. You’ll set the team’s technical and product direction, connect advances in machine learning to measurable business outcomes, and help engineers deliver reliable systems that balance loss prevention with the user experience. You’ll work across engineering, product, data science, and risk to identify the highest-impact opportunities and turn them into a focused roadmap. You’ll also hire and develop engineers, strengthen the team’s technical practices, and contribute to machine learning and engineering leadership across Stripe. Responsibilities Se

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Reddit
📍 United States• Remote• $292.5K – $409.5K/yr
1mo ago

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 About Reddit Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and 101M+ daily active unique visitors, we’re one of the largest sources of conversation and knowledge on the internet. For more information, visit redditinc.com . Team Overview The Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate. Our systems help ML engineers move faster across the full development lifecycle: creating features, generating training data, running offline experiments, validating model quality, launching production models, and operating ML systems reliably. We are looking for a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus will be on the feature development and training iteration loop: making it faster and easier for ML engineers to build features, generate reliable training data, run experiments, and move from idea to validated model improvement. Over time, this scope will expand into serving and online experimentation workflows, creating

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Lyft
📍 United States• Full-time
2mo ago

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

pythonmachine learninggolang
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At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

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About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Risk Detection is focused on providing a delightful experience for our merchants and minimizing friction, while ensuring the safety of our users in the financial ecosystem. Whenever the Risk team takes action on an account, we work to notify Merchants and provide clear status on what’s happening, enable guided workflows for resolving their issues, and redefine our overall Risk processes to make them as smooth as possible for good merchants. What you’ll do We’re looking for an engineering leader to lead and grow a strong team of engineers, build relationships with customers internally and externally, and champion our vision of making Stripe’s risk management a feature that attracts and retains merchants, and becomes a product differentiator. This is an exciting opportunity to partner with teams across Stripe to build the best merchant experience, and contribute directly to Stripe’s growth. Responsibilities Support the team in delivering a high level of technical quality and impact via APIs, user-facing experiences, services, and systems Recruit, hire, scale, and develop an amazing team of engineers Executing cross-functionally with leadership, product teams, infra teams & risk strategists Be actively involved in strategic direction and platform decisions that impact all of Stripe and Stripe customers Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you

machine learningaigo
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Pinterest
📍 United States• Full-time• Remote• $227.9K – $469.1K/yr
2mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We're looking for a highly technical Senior Engineering Manager with a deep understanding of modern recommendation systems to manage, lead and develop a team of ML researchers and engineers within the Applied Science team. In this role, you will lead the strategy of the Recommendation System innovation team. You will help the team build a balanced portfolio of work that addresses both immediate short-term business impact and long-term strategic breakthroughs in areas like Generative Recommendation System (GenRecSys), Large Sequential Models, and Reinforcement Learning (RL). Partnering closely with executive leadership, product management, and engineering partners, you will evolve our technical roadmap and directly drive Pinterest’s core mission forward. What you will do: Technical Vision and Execution: Own the tech

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About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Risk Detection is focused on providing a delightful experience for our merchants and minimizing friction, while ensuring the safety of our users in the financial ecosystem. Whenever the Risk team takes action on an account, we work to notify Merchants and provide clear status on what’s happening, enable guided workflows for resolving their issues, and redefine our overall Risk processes to make them as smooth as possible for good merchants. What you’ll do We’re looking for an engineering leader to lead and grow a strong team of engineers, build relationships with customers internally and externally, and champion our vision of making Stripe’s risk management a feature that attracts and retains merchants, and becomes a product differentiator. This is an exciting opportunity to partner with teams across Stripe to build the best merchant experience, and contribute directly to Stripe’s growth. Responsibilities Support the team in delivering a high level of technical quality and impact via APIs, user-facing experiences, services, and systems Recruit, hire, scale, and develop an amazing team of engineers Executing cross-functionally with leadership, product teams, infra teams & risk strategists Be actively involved in strategic direction and platform decisions that impact all of Stripe and Stripe customers Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you

machine learning
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Enigma
📍 New York• Full-time• $180K – $270K/yr
6mo ago

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index

pythonawsmachine learning
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Reddit
📍 United States• Remote• $292.5K – $409.5K/yr
6mo ago

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 . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform. Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably. Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions. Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience. Shape Reddit’s approach to an enterprise-grade RAG system Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform. Own the end-to-end platform strategy from concept t

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Twilio
📍 - US• Full-time• Remote• $155.5K – $194.4K/yr
7mo ago

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Machine Learning Engineer. About the job This position is needed to drive innovation and the development of cutting-edge products that serve developers, builders, and operators within Twilio’s Data & Observability Substrate organization. This is a hands-on, builder-focused engineering role that bridges Product, Design, and Engineering to develop, evaluate, and maintain scalable, low-latency, ML-based systems for real-time applications. You will lead rapid research-to-production cycles that translate business ideas into solutions for complex problems—such as streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks—with the goal of delivering personalized customer experiences. You will collaborate closely with a cross-functional team of engineers, architects, product managers, UI/UX designers, and ML/data science partners to deliver robust, reliable solutions that power c

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OpenAI
📍 San Francisco• Full-time
7mo ago

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

awsrestmachine learning
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