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Production Line Management Engineer Jobs

8,490 active opportunities · Updated for October 2026

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Explore current production line management engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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CLEAR - Corporate
📍 New York• Full-time• $175K – $215K/yr
3mo ago

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Senior Software Engineer to join our Network Engineering team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) by integrating new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, as well as implementing Kubernetes networking solutions like service mesh (Istio) to optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 6+ years of extensive experience in infrastructure and platform development, particularly in software-defined networking and AWS cloud services. Proficient in writing production-grade softwar

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DoorDash USA
📍 United States• Full-time• $139.4K – $205K/yr
3mo ago

About the Team DoorDash Labs is an independent innovation hub within DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. Our mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We are a highly senior team composed of former pioneers from a variety of different robotics industries. If you have a passion for applying AI and robotics solutions in a service used by millions of people, then we want to talk to you! Please Note: This role is based in San Francisco, CA, and requires being in-person 5 days a week. About the Role We are seeking a Senior RF Engineer to join our multidisciplinary team developing mission-critical RF/electrical systems for unmanned platforms.This role offers a rare opportunity to gain deep insight into RF design and validation, contributing across the full product lifecycle, from early concept and prototyping through production. In this role, you will apply deep expertise in electromagnetic theory and wireless system design to ensure autonomous platforms operate with exceptional reliability and precision. You will design, optimize and validate RF / mixed-signal PCBAs with a strong focus on interference mitigation, troubleshoot system-level desense, and leverage a thorough understanding of wireless technologies including LTE, 5G NR, Wi-Fi, GPS, and UWB. You’re excited about this opportunity because you will… Lead the development of innovative solutions that span across RF, Mixed signal and mechanical domain. Design RF hardware as well as wireless testbeds to support system validation, and lead the execution and documentation of system-level design and verification Provide expertise, mentorship to partner teams regarding EMI mitigation strategies, and cross-functional debug processes Characterize EMI caused by internal & external aggressors by tracing root causes using EMC probes

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MongoDB
📍 Gurugram• Full-time
3mo ago

The IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce development, platform governance, automation, and system operations, the team continuously enhances the CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Role Overview We are looking for a highly capable Senior Salesforce Engineer to design, build, and maintain scalable CRM solutions that support MongoDB’s Sales organization. This role combines strong hands-on Salesforce development, solution design, cross-functional collaboration, and a modern engineering mindset to deliver reliable, maintainable, and high-quality solutions across the core Salesforce platform. What you’ll do Design, build, and maintain scalable Salesforce solutions across the core CRM platform, including custom development, automation, and integrations Partner with business stakeholders, program managers, and technical teams to understand requirements and translate them into secure, maintainable, and scalable technical solutions Own delivery across the full solution lifecycle, including design, development, testing, deployment, documentation, and production support Collaborate closely with globally distributed engineering teams to deliver reliable, secure, and well-governed solutions in an Agile environment Drive strong engineering practices across code quality, documentation, release managem

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Coinbase
📍 - USA• Full-time• Remote• From $176K/yr
3mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . The Enterprise Applications & Architecture (EAA) Business Unit Delivery team builds and operates the internal platforms that help Coinbase scale. Within EAA, the Compliance CX Agent Experience team owns Agent Cockpit, the primary internal platform used by Coinbase's compliance agents and investigators to review cases, communicate with customers, access account and transaction data, and resolve compliance-related support queries. As a Staff Technical Program Manager, you'll own program delivery for this complex, high-impact platform, driving cross-functional execution to ensure agents and investigators have reliable, performant tools every day. What you'll do: Own the program management framework for Agent Cockpit, including roadmap tracking, intake and prioritization, sprint planning, dependency management, and cross-team delivery execution. Drive technical dependency coordination and platform migrations, translating upstream system changes (API deprecations, service integrations, data model changes) into internal delivery plans and engineering asks. Lead launch readiness and operational risk management, owning security review coordination, production approvals, testing governance, and escalation when critical-path items stall. Partner with Engineering on reliability, observability, and performance programs, including system health metrics, load testing, capacity

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Roblox
📍 San Mateo• Full-time• $399.4K – $458K/yr
3mo ago

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The platforms in our Engineering Acceleration org dictate how thousands of Roblox engineers ship, and how every backend service gets built, deployed, and kept reliable at scale. They sit on the critical path for production reliability, developer velocity, and security posture. Reporting to Andrew Swerdlow, you will rethink the entire engineering toolchain from the ground up to be agentic-native, creating a world where AI agents are first-class participants in software development and humans set direction and supervise. This is a unique opportunity to define what modern engineering infrastructure looks like at one of the largest platforms in the world. You will: Reimagine the engineering toolchain as agentic-native, designing the platforms, guardrails, and feedback loops that let AI agents safely drive migrations, validation, and routine operational work. Set a bold technical direction for AI-driven quality, including agent-generated tests, automated coverage of untested paths, intelligent verification, and continuous-deployment workflows. Make software quality and SEV prevention a measurable property of the platform by investing in safe-change mechanisms, automated verification, progressive

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Sayari
📍 United States• Remote• $160K – $180K/yr
3mo ago

About Sayari: Sayari is the judgment infrastructure for trustworthy AI in economic security and commercial risk. The Sayari Commercial World Model resolves 11.7B+ primary-source records from 250+ jurisdictions forming the ground truth of global commerce. A Judgment Ontology, encoding over a decade of investigative tradecraft, and Superconductor, an agentic orchestration platform, deliver AI that reasons like an expert analyst, shows its work, and traces every finding to its source. Trusted by U.S. Customs and Border Protection, HM Revenue & Customs, and Fortune 500 enterprises, Sayari is used by thousands of professionals across 35+ countries to secure supply chains and dismantle illicit networks. Headquartered in Washington, D.C., with offices in London, Singapore, Tokyo, and Tel Aviv. POSITION DESCRIPTION This is not a traditional engineering role. As a Forward Deployed Engineer (FDE), you are at the critical intersection of our code, our clients, and their most critical missions. You will be deployed to our most strategic partners, embedding within their environments to solve high-stakes problems that have no textbook answers. You own the "last mile" of our product's impact , ensuring our technology fundamentally transforms how our users confront challenges such as financial crime, supply chain disruption, and threats to national security. You are equal parts engineer, strategist, and operator. One day you might be architecting a data pipeline within a client's cloud environment ; the next, you'll be writing production Python to integrate our API into a proprietary analytics platform; and by the end of the week, you could be briefing a C-level executive, intelligence analyst, or mission director on the outcomes your work has enabled. You thrive on ambiguity, operate with extreme ownership, and are relentless in your pursuit of delivering real-world value. You will act as a vital conduit between the front lines and our core engineering teams, turning you

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Roblox
📍 San Mateo• Full-time• From $278.5K/yr
3mo ago

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. ML Platform @ Roblox today supports hundreds of ML use cases and billions of inferences per day across Discovery, Safety, Engine, and much more. As an Infrastructure Engineer on the ML Platform team, you will design, scale, and maintain the foundational infrastructure powering our entire machine learning ecosystem. We are looking for accomplished engineers to spearhead the development of our next-generation ML tooling and platform capabilities. You will: Bootstrap and maintain Kubernetes and Cloud infrastructure for ML Platform components--Serving Layer, Metadata Store, Model Registry, and Pipeline Orchestrator. Set technical strategy and oversee development of high scale and reliable infrastructure systems. Propose and implement new platform tooling to improve time to production for MLEs and Data Scientists across the full ML lifecycle. Work on infrastructure projects such as GPU fleet management, hybrid-cloud orchestration, and writing custom Kubernetes controllers and resources. Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices. Partner across organizations to build tooling, interfaces, and visualizati

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MongoDB
📍 Boston• Full-time• From $110K/yr
3mo ago

We’re looking for a dynamic and empowering Sales Development Manager who will be responsible for building and leading a team of enterprise ADRs. The role focuses on leadership, development and a high performance culture to execute against our rapid sales goals. The Opportunity In this role, you will have two core priorities: Talent Development & Revenue Development. We view our Account Development Representatives as the next wave of Account Executives at MongoDB. A Sales Development leader at MongoDB hires outstanding talent, maps out the gaps in that rep’s skillset, holds them accountable to reaching their potential, and takes pride in turning that ADR into an AE. You will also be a key asset to our Enterprise Sales organization, partnering with regional leaders across our sales organization, you will be a crucial part of uncovering new opportunities, determining how to unlock new territories, and driving revenue into our pipeline. We are looking to speak to candidates who are based in Boston for our hybrid working model. Day to Day Attract, hire, retain, and develop talent Provide strong coaching and mentoring through a deep understanding of sales, our business model, and our sales methodology. Be involved in prospect qualification and discovery calls/meetings Provide weekly team performance summary as well as timely and accurate forecast to senior management Cross functional collaboration to establish scalable processes for incoming lead management and follow-up SLAs and conversions Develop and own KPI’s, supervise the activity of the team, track the results and drive team execution based on those metrics Work closely with Field Sales and Inside Sales management to drive increased performance and align pipeline production to our Sales team's needs Invest in your self-development, focusing on the skills and attributes that will make you successful in your core role and get you set for future success What You Will Bring to the Table 2+ y

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Lyft
📍 Toronto• Full-time• From C$118.8K/yr
3mo 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. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see th

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Asana
📍 New York• Full-time• $248K – $282K/yr
3mo ago

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

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Asana
📍 San Francisco• Full-time• $248K – $282K/yr
3mo ago

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

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SpaceXSI
📍 Palo Alto• $180K – $440K/yr
3mo ago

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: The RL infrastructure team is looking for an engineer to help with low precision RL training and inference. RESPONSIBILITIES: Design and optimize our inference stack for all shapes of RL workloads at SpaceXSI, from small scale ablations to production training runs. Analyze, profile and address performance bottlenecks in large scale RL systems Work closely with the modelling team to efficiently implement novel RL techniques and algorithms BASIC QUALIFICATIONS: Experience in building, debugging, and optimizing efficiency of large-scale distributed systems Experience in LLM inference Proficiency in programming languages such as Python, C++ and/or Rust; frameworks such as PyTorch, Jax, CUDA Willingness to dive deep and solve hardcore problems at all levels of the stack PREFERRED SKILLS AND EXPERIENCE: Strong knowledge in quantization and numerics in LLM inference and training Experience in developing inference engines, e.g. SGLang, vLLM COMPENSATION AND BENEFITS: $180,000 - $440,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement pl

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Anthropic
📍 Ca New York City• $405K – $625K/yr
3mo ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Research Productivity organization builds the infrastructure and systems that accelerate research across Anthropic, including the tools that help our research process get faster and more effective over time. We're looking for an experienced software engineer to join us as we scale this infrastructure at a moment when both demand and scope are growing extremely quickly. This team operates like a startup within a startup. You'll be a strong fit if you like thinking from first principles, iterating fast on infrastructure, and tackling reliability and scalability challenges head-on as the products built on top of your systems evolve underneath you. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make the architectural decisions that shape how the infrastructure behind our research tooling gets built. You'll partner directly with research teams to understand their workflows, anticipate how their requirements will change, and design and scale infrastructure that can keep pace. Responsibilities Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams Make architectural decisions that shape the foundation of research infrastructure and tooling acr

machine learningailogistics
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3mo ago

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

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About Appier Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of "Making AI Easy by Making Software Intelligent," Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com . About the role Engineers at Appier build a wide range of platforms and services that interconnect data and AI with our customers and users—operating at scale where every millisecond and every nine of availability matters. As a Senior Backend Engineer (SRE / Reliability & Performance) , you will sit at the intersection of backend development and site reliability engineering: designing and building scalable, performant backend services while owning the reliability, observability, and performance characteristics of large-scale, high-traffic systems (QPS > 10k). You will profile and tune systems end to end, lead the response to production incidents, and drive the engineering practices that keep our services fast and resilient as traffic grows. Seniority and title are determined by job-related skills, experience, and evaluation following the interview. We welcome international candidates to our teams. This position is ideally to be based in Taiwan. Responsibilities Design and build scalable, reliable, and maintainable backend services and the components that support them Own system reliability and performance for high-traffic services, including SLO/SLA definition, error budgets, and capacity planning Profile, benchmark, and tune critical components to resolve latency, throughput, and scalability bottlenecks in medium-to-large systems (QPS > 10k) Diagnose and sol

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