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Deep understanding and taste of what good/useful Audio data is. Strong command of advanced transcription and annotation practices, including handling disfluencies, accents, and prosodic features (intonation, stress, rhythm, emotion, etc) with high consistency and accuracy. Background in linguistics (e.g., phonetics, phonology, sociolinguistics), speech sciences, cognitive science, or a related field, or equivalent practical experience, with demonstrated ability to analyse accent variation, pronunciation differences, and multilingual speech patterns. Experience working with speech/audio datasets, annotation workflows, or AI training data, including knowledge/experience with training voice models, and an understanding of how data quality impacts model performance. Professional experience in voice work, including voice acting, voice recording, podcasting with a measurable audience (e.g., X following), or similar audio production demonstrating attention to clarity and recording quality. Demonstrated ability to exercise independent judgment in ambiguous audio scenarios and make consistent, defensible annotation decisions. Portfolio (strongly preferred for advanced candidates): Voice samples, annotated transcripts, or audio-related work demonstrating quality, methodology, and attention to detail. Candidates with professional experience in voice, linguistics, speech data, or speech evaluation and research are especially encouraged to apply.</p>\n<p>Location and Other Expectations: Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit. For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average, most projects may require at least 10 hours per week to deliver effectively, though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables. Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role-specific needs. For US-based candidates, please note that we are unable to hire in Wyoming and Illinois at this time. We are unable to provide visa sponsorship. For those who will be working from a personal device, your computer must be a Chromebook, a Mac with macOS 11.0 or later, or Windows 10 or later.</p>\n<p>Compensation and Benefits: US-based candidates: $35/hour - $45/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process. Benefits vary based on employment type, location, and jurisdiction. Benefits for eligible U.S.-based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role-specific information will be provided to you during the interview process.</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_96e9554d-edc","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/5090171007","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time|part-time|contract","x-salary-range":"$35/hour - $45/hour","x-skills-required":["Multilingual audio capabilities","Proprietary software","Audio data curation","Annotation tools","Speech recognition","Auditory experiences","Natural language processing","Accent variation","Noise reduction","Multilingual audio processing"],"x-skills-preferred":["Linguistic nuance","Auditory detail","Data quality","Advanced transcription and annotation practices","Disfluencies","Accents","Prosodic features","Linguistics","Speech sciences","Cognitive science","Voice work","Voice acting","Voice recording","Podcasting"],"datePosted":"2026-04-18T15:52:57.094Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Multilingual audio capabilities, Proprietary software, Audio data curation, Annotation tools, Speech recognition, Auditory experiences, Natural language processing, Accent variation, Noise reduction, Multilingual audio processing, Linguistic nuance, Auditory detail, Data quality, Advanced transcription and annotation practices, Disfluencies, Accents, Prosodic features, Linguistics, Speech sciences, Cognitive science, Voice work, Voice acting, Voice recording, Podcasting"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_aa930f92-8cf"},"title":"Pure Math Tutor","description":"<p>As an AI Tutor - Pure Math Specialist, you&#39;ll play a key role in advancing xAI&#39;s mission by enhancing our AI technologies through high-quality inputs, labels, and annotations using specialized software.</p>\n<p>You&#39;ll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create complex problems from advanced pure math topics to boost performance.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Using proprietary software applications to provide input/labels on defined projects.</li>\n<li>Supporting and ensuring the delivery of high-quality curated data.</li>\n<li>Playing a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.</li>\n<li>Interacting with the technical staff to help improve the design of efficient annotation tools.</li>\n<li>Choosing problems from pure math subdomains that align with your expertise, focusing on areas like abstract algebra, real/complex analysis, topology, graph theory, and so on where you can confidently provide detailed solutions and evaluate model responses.</li>\n</ul>\n<p>To succeed in this role, you&#39;ll need:</p>\n<ul>\n<li>A Master&#39;s or PhD in Mathematics with a specialization in a subdomain of pure mathematics, or a medal in an International Math Olympiad (IMO) or similar level math competition.</li>\n<li>Proficiency in reading and writing, both in informal and professional English.</li>\n<li>Strong ability to navigate various information resources and databases.</li>\n<li>Outstanding communication, interpersonal, analytical, and organizational capabilities.</li>\n<li>Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.</li>\n</ul>\n<p>Preferred skills and experience include:</p>\n<ul>\n<li>Math PhD with a specialization in a subdomain of pure mathematics.</li>\n<li>Peer-reviewed pure math publications in well-regarded journals.</li>\n<li>Previous AI Tutoring experience and/or experience teaching college courses.</li>\n</ul>\n<p>As a remote worker, you&#39;ll have the flexibility to set your own hours and determine the exact amount of time needed to complete deliverables. 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The team builds the training environments that fuel RL at scale. This is a unique role that combines executing directly on ML research, data operations, and project management to improve our models. You&#39;ll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Improve and execute our fine-tuning strategies for adapting Claude to new domains and tasks</li>\n<li>Manage technical relationships with external data vendors, including evaluation of data quality and reward design</li>\n<li>Collaborate with domain experts to design data pipelines and evaluations</li>\n<li>Explore novel ways of creating RL environments for high value tasks</li>\n<li>Develop and improve QA frameworks to catch reward hacking and ensure environment quality</li>\n<li>Partner with other RL research teams and product teams to translate capability goals into training environments and evals</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have experience with fine-tuning large language models for specific domains or real-world use cases and/or domain expertise in an area where we would like to make our models more useful.</li>\n<li>Have experience with reinforcement learning, reward design, or training data curation for LLMs</li>\n<li>Are comfortable managing technical vendor relationships and iterating quickly on feedback</li>\n<li>Find value in reading through datasets to understand them and spot issues</li>\n<li>Have strong project management and interpersonal skills</li>\n<li>Are passionate about making AI more useful and accessible across different industries</li>\n<li>Are excited about a role that includes a combination of ML research, data operations, and project management</li>\n</ul>\n<p><strong>Strong candidates may also:</strong></p>\n<ul>\n<li>Have experience training production ML systems</li>\n<li>Be familiar with distributed systems and cloud infrastructure</li>\n<li>Have domain expertise in an area where we would like to make our models more useful</li>\n<li>Have experience working with external vendors or technical partners</li>\n</ul>\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. 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.</strong></p>\n<p><strong>Your safety matters to us. 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.</strong></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. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco, CA.</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_912450ea-c61","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4951064008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000 - $850,000USD","x-skills-required":["fine-tuning large language models","reinforcement learning","reward design","training data curation","project management","interpersonal skills"],"x-skills-preferred":["experience training production ML systems","distributed systems and cloud infrastructure","domain expertise in an area where we would like to make our models more useful","experience working with external vendors or technical partners"],"datePosted":"2026-03-08T13:47:17.433Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"fine-tuning large language models, reinforcement learning, reward design, training data curation, project management, interpersonal skills, experience training production ML systems, distributed systems and cloud infrastructure, domain expertise in an area where we would like to make our models more useful, experience working with external vendors or technical partners","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d446c7ab-5f0"},"title":"Member of Technical Staff, Applied Scientist - Windows Copilot","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Member of Technical Staff, Applied Scientist - Windows Copilot at their Redmond office. This role sits at the heart of redefining how AI enhances everyday computing. You&#39;ll work directly with leadership to shape the company&#39;s direction in the Windows Copilot team.</p>\n<p><strong>About the Role</strong></p>\n<p>The Windows Copilot team is at the forefront of redefining how AI enhances everyday computing. This team owns the full stack—from cutting-edge AI infrastructure and model development, to crafting seamless user experiences directly in Windows. We’re building and shipping consumer-scale services that are transforming how users interact with their PCs. Whether it’s designing intelligent prompts, engineering robust backends to interface with models, or developing native Windows platform and UX features, this team does it all.</p>\n<p>As an Applied Scientist, you will lead the end-to-end model-building process, including problem understanding, data curation, model development, deployment, and iteration based on real-world feedback. This role will serve as a critical bridge between Microsoft Research and the engineering team, taking increasing ownership of model training responsibilities.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and refine data pipelines and infrastructure to support AI model development for Copilot.</li>\n<li>Collaborate with research teams to integrate cutting-edge AI advancements into production systems.</li>\n<li>Design, train, and evaluate machine learning models, ensuring performance optimization and scalability.</li>\n<li>Work closely with engineering and product teams to ensure AI-driven experiences meet quality and user experience standards.</li>\n<li>Conduct rigorous data analysis and experimentation, leveraging insights to improve Copilot’s intelligence.</li>\n<li>Overcome obstacles to deliver iterative improvements in AI performance and responsiveness.</li>\n<li>Stay ahead of the latest innovations in deep learning, reinforcement learning, and generative AI.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven track record of deploying machine learning models in large-scale production environments.</li>\n<li>9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n<li>Ability to work in a fast-paced environment and adapt to changing priorities.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range: $119,800 - $234,700 per year.</li>\n<li>Comprehensive benefits package, including medical, dental, and vision insurance.</li>\n<li>401(k) matching program.</li>\n<li>Paid time off and holidays.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</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_d446c7ab-5f0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-applied-scientist-windows-copilot/","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["machine learning","deep learning","data pipelines","data curation","model development","deployment","iteration","research","statistics","econometrics","computer science","electrical engineering","computer engineering"],"x-skills-preferred":["proven track record of deploying machine learning models in large-scale production environments","9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows"],"datePosted":"2026-03-06T07:26:56.178Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, data pipelines, data curation, model development, deployment, iteration, research, statistics, econometrics, computer science, electrical engineering, computer engineering, proven track record of deploying machine learning models in large-scale production environments, 9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}}]}