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Since 2018, we&#39;ve been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.</p>\n<p>We&#39;re the only company offering three integrated solutions for frontier AI development:</p>\n<ul>\n<li>Enterprise Platform &amp; Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale</li>\n</ul>\n<ul>\n<li>Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models</li>\n</ul>\n<ul>\n<li>Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling</li>\n</ul>\n<p>Why Join Us</p>\n<ul>\n<li>High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. 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This includes building a platform that enables us and our customers to create and evaluate data, as well as systems that leverage LLMs to assist with reviewing, scoring, and improving human submissions.</p>\n<p>Your Impact</p>\n<ul>\n<li>Own End-to-End Product Features</li>\n</ul>\n<p>Design, build, and ship complete workflows spanning frontend UI, APIs, backend services, databases, and production infrastructure.</p>\n<ul>\n<li>Enable Human-in-the-Loop AI Training</li>\n</ul>\n<p>Build systems that allow humans to efficiently create, review, and curate high-quality training and evaluation data used in AI model development.</p>\n<ul>\n<li>Support RLHF and Preference Data Workflows</li>\n</ul>\n<p>Design and implement tooling that supports RLHF-style pipelines, including task generation, human review, scoring, aggregation, and dataset versioning.</p>\n<ul>\n<li>Leverage LLMs in the Review Loop</li>\n</ul>\n<p>Build systems that use LLMs to assist human reviewers,such as automated checks, critiques, ranking suggestions, or quality signals,while maintaining human oversight.</p>\n<ul>\n<li>Advance AI Evaluation</li>\n</ul>\n<p>Design and implement evaluation frameworks and interactive tools for LLMs and AI agents across multiple data modalities (text, images, audio, video).</p>\n<ul>\n<li>Create Intuitive, Reviewer-Focused Interfaces</li>\n</ul>\n<p>Build thoughtful, efficient user interfaces (e.g., in React) optimized for high-throughput human review, quality control, and operational workflows.</p>\n<ul>\n<li>Architect Scalable Data &amp; Service Layers</li>\n</ul>\n<p>Design APIs, backend services, and data schemas that support large-scale data creation, review, and iteration with strong guarantees around correctness and traceability.</p>\n<ul>\n<li>Solve Ambiguous, Real-World Problems</li>\n</ul>\n<p>Translate loosely defined operational and research needs into practical, scalable, end-to-end systems.</p>\n<ul>\n<li>Ensure System Reliability</li>\n</ul>\n<p>Participate in on-call rotations to monitor, troubleshoot, and resolve issues across the full stack.</p>\n<ul>\n<li>Elevate the Team</li>\n</ul>\n<p>Improve engineering practices, development processes, and documentation. 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Our team combines deep technical expertise with a passion for innovation, working at the intersection of AI infrastructure, data systems, and user experience. We believe in pushing technical boundaries while maintaining high standards of code quality and system reliability. Our engineering culture emphasizes autonomous decision-making, rapid iteration, and collaborative problem-solving. We&#39;ve cultivated an environment where engineers can take ownership of significant challenges, experiment with cutting-edge technologies, and see their solutions directly impact how leading AI labs and enterprises build the next generation of AI systems.</p>\n<p>Our Technology Stack</p>\n<p>Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency:</p>\n<ul>\n<li>Frontend: React.js with Redux, TypeScript</li>\n</ul>\n<ul>\n<li>Backend: Node.js, TypeScript, Python, some Java &amp; Kotlin</li>\n</ul>\n<ul>\n<li>APIs: GraphQL</li>\n</ul>\n<ul>\n<li>Cloud &amp; Infrastructure: Google Cloud Platform (GCP), Kubernetes</li>\n</ul>\n<ul>\n<li>Databases: MySQL, Spanner, PostgreSQL</li>\n</ul>\n<ul>\n<li>Queueing / Streaming: Kafka, PubSub</li>\n</ul>\n<p>Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. 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Not all strong candidates will meet every single qualification as listed.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_bd9625d9-99b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4778843008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["Python","PyTorch","TensorFlow","JAX","Cloud platforms (AWS, GCP)","Container orchestration (Kubernetes)","Distributed systems principles","Data engineering tools (Spark, Airflow, streaming systems)"],"x-skills-preferred":["Large language models and modern transformer architectures","A/B testing frameworks and experimentation infrastructure for ML systems","Monitoring and alerting systems for ML model performance and data drift","Automated labeling systems and human-in-the-loop workflows","Trust & safety, fraud prevention, or content moderation domains","Privacy-preserving ML techniques and compliance requirements","Open-source ML infrastructure projects"],"datePosted":"2026-04-18T15:44:06.907Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, JAX, Cloud platforms (AWS, GCP), Container orchestration (Kubernetes), Distributed systems principles, Data engineering tools (Spark, Airflow, streaming systems), Large language models and modern transformer architectures, A/B testing frameworks and experimentation infrastructure for ML systems, Monitoring and alerting systems for ML model performance and data drift, Automated labeling systems and human-in-the-loop workflows, Trust & safety, fraud prevention, or content moderation domains, Privacy-preserving ML techniques and compliance requirements, Open-source ML infrastructure projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1485bbbe-6b5"},"title":"Member of Technical Staff - X Money","description":"<p>Join our X Money team as a talented Software Engineer to build a revolutionary global payment network serving over 600 million users. 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Uphold engineering excellence via testing, monitoring, deployment, and secure data handling.</p>\n<p>Basic Qualifications: Proficiency in distributed systems for high-scale, low-latency environments; languages like Rust, Go, Python &amp; Java, and high volume streaming systems. 2+ years of experience working on large scale consumer applications.</p>\n<p>Preferred Skills and Experience: 5+ years of experience working on large scale consumer applications or early-mid stage startup experience as a founding engineer, emphasising rapid prototyping, user-centric design, and AI solutions.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_1485bbbe-6b5","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com/","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/5107958007","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - $440,000 USD","x-skills-required":["distributed systems","Rust","Go","Python","Java","high volume streaming systems"],"x-skills-preferred":["rapid prototyping","user-centric design","AI solutions"],"datePosted":"2026-04-18T15:24:03.451Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, NY; Palo Alto, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"distributed systems, Rust, Go, Python, Java, high volume streaming systems, rapid prototyping, user-centric design, AI solutions","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":440000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5f44ff2b-0f4"},"title":"Member of Technical Staff - X Money","description":"<p>Join our X Money team as a Software Engineer to build a revolutionary global payment network serving over 600 million users. You will specialise in backend development, designing and optimising robust microservices for scalability, security, and reliability. Collaborate with cross-functional teams on payments, fraud detection, and compliance initiatives, and contribute to the creation of a high-scale financial products platform.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Develop backend services, APIs, and data models to support high-volume, multi-user environments.</li>\n<li>Work with iOS, Android &amp; Web client engineers to ship products.</li>\n<li>Design robust infrastructure and microservices for payments, transactions, growth, monetization, and engagement across platforms.</li>\n<li>Build and maintain fullstack features, including user dashboards, personalised experiences, content delivery, interactive tools, assessments, and real-time analytics.</li>\n<li>Lead architecture, scalability, and reliability decisions for high-concurrency, low-latency systems.</li>\n<li>Uphold engineering excellence via testing, monitoring, deployment, and secure data handling.</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>Proficiency in distributed systems for high-scale, low-latency environments; languages like Rust, Go, Python &amp; Java, and high volume streaming systems.</li>\n<li>2+ years of experience working on large scale consumer applications.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_5f44ff2b-0f4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com/","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/5108231007","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Rust","Go","Python","Java","high volume streaming systems"],"x-skills-preferred":["distributed systems","low-latency environments","rapid prototyping","user-centric design","AI solutions"],"datePosted":"2026-04-18T15:23:55.431Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"Rust, Go, Python, Java, high volume streaming systems, distributed systems, low-latency environments, rapid prototyping, user-centric design, AI solutions"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ccc87f8c-abf"},"title":"Member of Technical Staff – X Core Product","description":"<p><strong>About the Role</strong></p>\n<p>As a Member of Technical Staff on the X Core Product team, you&#39;ll join a thirty-person team responsible for building and scaling X. You will be tasked with independently owning significant parts of the system end-to-end: from intuitive user interfaces to robust backend services, data infrastructure, and deep AI integrations.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Develop backend services, APIs, and data models to support high-volume, multi-user environments.</li>\n<li>Work with iOS, Android &amp; Web client engineers to ship products.</li>\n<li>Design robust infrastructure and microservices for payments, transactions, growth, monetization, and engagement across platforms.</li>\n<li>Build and maintain fullstack features, including user dashboards, personalized experiences, content delivery, interactive tools, assessments, and real-time analytics.</li>\n<li>Lead architecture, scalability, and reliability decisions for high-concurrency, low-latency systems.</li>\n<li>Uphold engineering excellence via testing, monitoring, deployment, and secure data handling.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Proficiency in distributed systems for high-scale, low-latency environments; languages like Rust, Go, Python &amp; Java, and high volume streaming systems.</li>\n<li>2+ years of experience working on large scale consumer applications.</li>\n</ul>\n<p><strong>Preferred Skills and Experience</strong></p>\n<ul>\n<li>5+ years of experience working on large scale consumer applications or early-mid stage startup experience as a founding engineer, emphasizing rapid prototyping, user-centric design, and AI solutions.</li>\n</ul>\n<p><strong>Compensation and Benefits</strong></p>\n<p>$180,000 - $440,000 USD</p>\n<p>Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short &amp; long-term disability insurance, life insurance, and various other discounts and perks.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ccc87f8c-abf","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com/","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/5063929007","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - $440,000 USD","x-skills-required":["distributed systems","Rust","Go","Python","Java","high volume streaming systems"],"x-skills-preferred":["rapid prototyping","user-centric design","AI solutions"],"datePosted":"2026-04-18T15:23:48.306Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"distributed systems, Rust, Go, Python, Java, high volume streaming systems, rapid prototyping, user-centric design, AI solutions","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":440000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_672557eb-bee"},"title":"Engineering Manager, Data Platform","description":"<p><strong>Engineering Manager, Data Platform</strong></p>\n<p>We&#39;re looking for an experienced Engineering Manager to lead our Data Interfaces team, responsible for enabling users and systems to leverage our core data platform. The team owns the collection of operational telemetry data, the UI for interacting with the Data Platform, as well as APIs and plugins for querying data out of the Data Platform for visualization, alerting, and integration into internal services.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Lead, mentor, and grow a team of senior and principal engineers</li>\n<li>Foster an inclusive, collaborative, and feedback-driven engineering culture</li>\n<li>Drive continuous improvement in the team&#39;s processes, delivery, and impact</li>\n<li>Collaborate with stakeholders in engineering, data science, and analytics to shape and communicate the team&#39;s vision, strategy, and roadmap</li>\n<li>Bridge strategic vision and tactical execution by breaking down long-term goals into achievable, well-scoped iterations that deliver continuous value</li>\n<li>Ensure high standards in system architecture, code quality, and operational excellence</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>3+ years of engineering management experience leading high-performing teams in data platform or infrastructure environments</li>\n<li>Proven track record navigating complex systems, ambiguous requirements, and high-pressure situations with confidence and clarity</li>\n<li>Deep experience in architecting, building, and operating scalable, distributed data platforms</li>\n<li>Strong technical leadership skills, including the ability to review architecture/design documents and provide actionable feedback on code and systems</li>\n<li>Ability to engage deeply in technical discussions, review architecture and design documents, evaluate pull requests, and step in during high-priority incidents when needed — even if hands-on coding isn’t a part of the day-to-day</li>\n<li>Hands-on experience with distributed event streaming systems like Apache Kafka</li>\n<li>Familiarity with OLAP databases such as Apache Pinot or ClickHouse</li>\n<li>Proficient in modern data lake and warehouse tools such as S3, Databricks, or Snowflake</li>\n<li>Strong foundation in the .NET ecosystem, container orchestration with Kubernetes, and cloud platforms, especially AWS</li>\n<li>Experience with distributed data processing engines like Apache Flink or Apache Spark is nice to have</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<p>Epic Games offers a comprehensive benefits package, including:</p>\n<ul>\n<li>100% coverage of medical, dental, and vision premiums for you and your dependents</li>\n<li>Long-term disability and life insurance</li>\n<li>401k with competitive match</li>\n<li>Unlimited PTO and sick time</li>\n<li>Paid sabbatical after 7 years of employment</li>\n<li>Robust mental well-being program through Modern Health</li>\n<li>Company-wide paid breaks and events throughout the year</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_672557eb-bee","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Epic Games","sameAs":"https://www.epicgames.com","logo":"https://logos.yubhub.co/epicgames.com.png"},"x-apply-url":"https://www.epicgames.com/en-US/careers/jobs/5818031004","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["engineering management","data platform","distributed event streaming systems","OLAP databases","modern data lake and warehouse tools",".NET ecosystem","container orchestration","cloud platforms"],"x-skills-preferred":["Apache Kafka","Apache Pinot","ClickHouse","S3","Databricks","Snowflake","Kubernetes","AWS","Apache Flink","Apache Spark"],"datePosted":"2026-03-08T22:16:11.037Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Cary"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"engineering management, data platform, distributed event streaming systems, OLAP databases, modern data lake and warehouse tools, .NET ecosystem, container orchestration, cloud platforms, Apache Kafka, Apache Pinot, ClickHouse, S3, Databricks, Snowflake, Kubernetes, AWS, Apache Flink, Apache Spark"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6cc383e0-ff6"},"title":"ML Infrastructure Engineer, Safeguards","description":"<p><strong>About the role</strong></p>\n<p>We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you&#39;ll build and scale the critical infrastructure that powers our AI safety systems. You&#39;ll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem</li>\n<li>Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications</li>\n<li>Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems</li>\n<li>Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards</li>\n<li>Implement automated testing, deployment, and rollback systems for ML models in production safety applications</li>\n<li>Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs</li>\n<li>Contribute to the development of internal tools and frameworks that accelerate safety research and deployment</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment</li>\n<li>Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX</li>\n<li>Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)</li>\n<li>Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads</li>\n<li>Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)</li>\n<li>Are results-oriented, with a bias towards reliability and impact in safety-critical systems</li>\n<li>Enjoy collaborating with researchers and translating cutting-edge research into production systems</li>\n<li>Care deeply about AI safety and the societal impacts of your work</li>\n</ul>\n<p><strong>Strong candidates may have experience with:</strong></p>\n<ul>\n<li>Working with large language models and modern transformer architectures</li>\n<li>Implementing A/B testing frameworks and experimentation infrastructure for ML systems</li>\n<li>Developing monitoring and alerting systems for ML model performance and data drift</li>\n<li>Building automated labeling systems and human-in-the-loop workflows</li>\n<li>Experience in trust &amp; safety, fraud prevention, or content moderation domains</li>\n<li>Knowledge of privacy-preserving ML techniques and compliance requirements</li>\n<li>Contributing to open-source ML infrastructure projects</li>\n</ul>\n<p><strong>Deadline to apply:</strong></p>\n<p>None. Applications will be reviewed on a rolling basis.</p>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong></p>\n<p>Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work.</p>\n<p><strong>Your safety matters to us.</strong></p>\n<p>To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. 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