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Applied Ai Architects Manager Jobs

1,018 active opportunities · Updated for October 2026

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Explore current applied ai architects manager jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Brex
📍 San Francisco• $119.3K – $149.2K/yr
21 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. What You’ll Do Account Servicing owns what happens to a Brex account after it's live: money applied against statement balances, billing terms changed, auto-pay kept working, points debited and granted, credit performance reported to the bureaus, and accounts closed cleanly. We're hiring a manager to run that portfolio. You'll inherit a team with deep subject-matter expertise in specific queues, a set of in-flight migrations from other teams, and a

sqlaisalesforce
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Brex
📍 Salt Lake City• $105.6K – $132K/yr
21 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. What You’ll Do Account Servicing owns what happens to a Brex account after it's live: money applied against statement balances, billing terms changed, auto-pay kept working, points debited and granted, credit performance reported to the bureaus, and accounts closed cleanly. We're hiring a manager to run that portfolio. You'll inherit a team with deep subject-matter expertise in specific queues, a set of in-flight migrations from other teams, and a

sqlaisalesforce
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B
Brex
📍 New York• $119.3K – $149.2K/yr
21 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. What You’ll Do Account Servicing owns what happens to a Brex account after it's live: money applied against statement balances, billing terms changed, auto-pay kept working, points debited and granted, credit performance reported to the bureaus, and accounts closed cleanly. We're hiring a manager to run that portfolio. You'll inherit a team with deep subject-matter expertise in specific queues, a set of in-flight migrations from other teams, and a

sqlaisalesforce
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B
Brex
📍 Seattle• $119.3K – $149.2K/yr
21 days ago

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. What You’ll Do Account Servicing owns what happens to a Brex account after it's live: money applied against statement balances, billing terms changed, auto-pay kept working, points debited and granted, credit performance reported to the bureaus, and accounts closed cleanly. We're hiring a manager to run that portfolio. You'll inherit a team with deep subject-matter expertise in specific queues, a set of in-flight migrations from other teams, and a

sqlaisalesforce
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R
Reddit
📍 United States• Remote• $230K – $322K/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 . Team Description: The Ads Retrieval ML team builds the machine learning systems that identify relevant advertising candidates for Reddit users. Retrieval sits at the heart of the ads delivery funnel: before downstream ranking and auction decisions, our models determine which campaigns and ads are eligible to compete. We work on large-scale retrieval across multiple objectives, placements, and geographies. Our work combines representation learning, candidate generation, nearest-neighbor search, behavioral and contextual signals, and rigorous offline and online experimentation. Role Description: We are looking for a Staff Machine Learning Engineer to provide technical leadership for the Retrieval ML team. You will lead the design and evolution of retrieval models and modeling practices that improve relevance, advertiser outcomes, and user experience at Reddit scale. This is an applied ML role centered on retrieval modeling and end-to-end product impact. You will be expected to stay close to the technical details—from data and objective design through model development, evaluation, experimentation, and launch—while setting direction for other engineers. Responsibilities: Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders. Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit’s advertising surfaces. Apply modern approaches such as two-tower architectures, repres

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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 Synthesia Roleplay Sessions is a training tool that lets people practice real conversations with AI avatars. Instead of just watching training videos, learners do interactive roleplay exercises, like practicing a sales pitch or handling a customer complaint with an AI coach. The AI gives instant feedback so people know what they did well and what to improve. Managers can use a dashboard to track which employees have completed their training, see how well they performed, and measure if the training actually improved their skills. The whole platform is built around learning by doing rather than just passive video watching. For your ML engineer role, you'd be building the AI engine that makes the coaching work. That means creating the models that listen to what learners say during roleplay, score their performance, generate helpful feedback in real time, and decide how the AI avatar should respond next based on what the learner does. This is an applied ML position, not a research one . We expect you to have a good understanding of ML but on the other side to be a good product-focused software developer as you will be expected to work on different products. Please bring with you: Ability to apply your

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Eulerity is a rapidly growing technology company revolutionizing marketing automation for small businesses and franchises with our industry-leading proprietary software. We were founded by leaders from Google, Facebook and Yahoo! with more than 20 years of digital advertising, engineering and marketing experience. Your Role: Take an active role in developing, testing, and maintaining our backend services — leveraging AI agents to accelerate and improve your work Implementing new features, starting from design to deployment Help come up with new features and product ideas, using AI tooling to prototype and iterate quickly Collaborate with other teams on features and releases Assist with the preparation of documentation, training, and support of various systems About You: You have at least hands-on experience working with AI agents (e.g. Claude, Copilot, Cursor, or similar coding agents) to build, debug, and improve software Experience with LLMs, AI agent frameworks, or AI-assisted product development (you've actually used these, not just read about them) At least 1 year of experience building backend solutions with Java You have a strong willingness to continuously learn, experiment with, and deepen your knowledge of AI tools and how they can be applied to real engineering challenges You understand how to use agents and LLMs to find the right resources, generate and review code, and solve problems more effectively You enjoy coming up with creative solutions to complex problems Comfortable integrating with third-party APIs Able to work in conjunction with other team members Great communication skills and a friendly disposition Requirements: Based in the NYC tri-state area Able to commit minimum 20 hours per week Benefits: Pay $18-$20/hour Mentorship with regular peer review sessions Unlimited snacks and an in office lunch credit. Full GitHub Copilot access with frontier LLMs and coding agents from Anthropic, Google, and OpenAI — keeping you equipped with the best AI t

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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team OpenAI's Research Team is at the forefront of AI research, pushing the limits of what AI can achieve. Our team is dedicated to developing advanced AI systems that are powerful, safe, and beneficial for everyone. About the Role The Research IP Partnerships team is in need of Technical Program Managers (TPMs) to streamline the integration of our applied research with external strategic partners. This role is critical for synthesizing research from cross functional teams, enabling model deployment, and ensuring new technologies are effectively adopted. You will act as the connection that enables our partners to deploy the most advanced AI models. Your primary focus will be to increase our research velocity and ensure that our deployments are successful and collaborative with our partners. This role is based in San Francisco, CA. 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: Build and share a deep understanding of frontier AI model development Partner with internal and external teams to drive deployment of the latest OpenAI technologies Manage critical inquiries from both technical and non-technical partners Design and implement simple, scalable processes that solve complex problems Deliver high-profile pipeline and tooling projects on tight deadlines Work across research and engineering to align goals, streamline communication, and support business priorities You might thrive in this role if you: Have experience in a strategic partnerships and technical program management role Can right-size process to align stakeholders while ensuring speed of delivery (action-oriented) Are fantastic at building cross-functional relationships and having empathy for the many roles involved in deploying research Can design and build tools (via code / no-code / AI) to facilitate internal processes Are a great communicator across written, presentation, and visual forms. Are engaged and c

awsrestai
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OpenAI
📍 San Francisco• Full-time• $239K – $328K/yr
1mo ago

About the Team OpenAI’s Research Program Management team partners with researchers and engineers to advance the development of increasingly capable, safe, and beneficial AI systems. We work alongside teams developing our core models, helping turn ambitious research goals into coordinated execution across model training, alignment and safety, and research infrastructure. The team also regularly collaborates with our closest cross-functional partners such as Security, Applied product and engineering, Strategy, and Scaling. About the Role As a Research Program Manager, you will embed with research teams and help drive some of the most technically complex and consequential work behind OpenAI’s model development. Depending on your focus, your work may span training, reasoning, evaluations, compute, research infrastructure, safety, model launch readiness, and governance. You will translate evolving research priorities into actionable programs, help teams navigate technical and operational tradeoffs, and keep important work moving as new issues emerge. This is a hands-on technical role: you will engage directly with research workflows, experimental results, technical systems, and engineering constraints; not simply coordinate from the sidelines. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: Have 5+ years of experience in research program management, technical program management, or related roles in fast-moving environments. Can engage substantively with researchers and engineers on topics such as model training, experimental design, model safety, evaluation methods, data workflows, compute infrastructure, or distributed systems. Are comfortable working directly with technical tools, research data, experimental results, or operational workflows to understand problems and develop practical solutions. Have a strong track record of movi

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Who we are About the team Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers. What you'll do We're looking for machine learning engineers who want to build intelligent systems that provide financial data at scale. You'll play a key role in designing, training, and deploying ML models that improve the quality, accuracy, and usefulness of financial data across Stripe's ecosystem. Responsibilities Design, build, train, evaluate, deploy, and own ML models in production that improve transaction categorization, risk scoring, and data enrichment across Financial Connections Design and build large-scale ML systems that operate on diverse financial data from thousands of institutions Experiment and iterate on ML models (using tools such as PyTorch, TensorFlow, XGBoost) to achieve key business goals around data quality and accuracy Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliability Collaborate with product, data science, and engineering partners across Stripe to identify opportunities where ML can im

machine learningai
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Blocktech
📍 Amsterdam• Full-time
1mo ago

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern

pythonaigo
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Blocktech
📍 Singapore, Singapore• Full-time
1mo ago

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m

pythonaigo
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O
OpenAI
📍 San Francisco• Full-time
2mo ago

About the Team OpenAI is a frontier AI research and deployment company. Frontier research is at the center of how we advance our mission, with researchers, engineers, product leaders, operators, and many other teams working together to turn new capabilities into systems that benefit humanity. The People team helps OpenAI attract, engage, and support the exceptional talent this work requires. Employer Brand sits at the intersection of Research, Recruiting, Communications, Marketing, and Brand. Its mandate is to continue to establish OpenAI in the talent market as the unique and leading frontier research lab—not simply another technology company—and make our distinctive research environment, mission, culture, and opportunity for impact relevant and tangible to every priority talent audience. About the Role We’re hiring an Employer Brand Manager to build and scale the strategy, narrative, and operating system that shape how priority talent understands OpenAI. This senior individual contributor will anchor our employer brand in OpenAI’s identity as a frontier research lab and translate an evidence-backed “why OpenAI / why now” narrative into campaigns, researcher and employee stories, recruiter and hiring manager enablement, and candidate experiences. This role is especially important as OpenAI competes for exceptional talent across research, engineering, product, and other mission-critical functions in a fast-moving field where external perceptions can be incomplete or change quickly. You will develop a clear, credible talent narrative for priority audiences—anchored in frontier research and substantiated by individual agency, world-class infrastructure, research-to-product translation, deployment scale, and a willingness to answer hard questions candidly. This role is responsible for ensuring the external brand resembles our culture and ethos internally, therefore must remain immersed in various OpenAI research and applied branches. This role is based in San Francisco

awsrestai
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O
OpenAI
📍 San Francisco• Full-time• $380K – $500K/yr
2mo ago

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, your work will span memory architecture, post-training, and developing long-horizon tasks for training and evaluations. We're looking for individuals who have a background in reinforcement learning research, are able to iterate quickly, and who can convert scientific rigor and long-term research into realized product impact. This role is based in San Francisco, CA. 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: Own and pursue a research agenda for improving long-horizon memory and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Love being on the cutting edge of RL and frontier model research. Value principled approaches and research craftsmanship. Are passionate about long-horizon tasks, memory, and turning your research into product impact. Are comfortable diving into a large ML codebase to debug. Thrive in a fast-paced, dynamic, and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI syst

artificial intelligenceai
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S
Stripe
📍 Toronto• Full-time
3mo ago

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 Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team’s work from this recent talk . What you’ll do As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community. Responsibilities Our team operates fluidly and here are some problems you may tackle: How do we evaluate a system offline & online? How do we improve performance to match (and beat) humans? How do we ensure model quality doesn’t degrade online? Does fine-tuning an LLM give us better performance? What are the right OSS and in-house platforms we should invest in? And in the process you will: Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliab

machine learningai
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