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Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have hands-on experience with training audio models, whether that&#39;s conversational speech-to-speech, speech translation, speech recognition, text-to-speech, diarization, codecs, or generative audio models</li>\n<li>Genuinely enjoy both research and engineering work, and you&#39;d describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other</li>\n<li>Are comfortable working across abstraction levels, from signal processing fundamentals to large-scale model training and inference optimization</li>\n<li>Have deep expertise with JAX, PyTorch, or large-scale distributed training, and can debug performance issues across the full stack</li>\n<li>Thrive in fast-moving environments where the most important problem might shift as we learn more about what works</li>\n<li>Communicate clearly and collaborate effectively; audio touches many parts of our systems, so you&#39;ll work closely with teams across the company</li>\n<li>Are passionate about building conversational AI that feels natural, steerable, and safe</li>\n<li>Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>Large language model pretraining and finetuning</li>\n<li>Training diffusion models for image and audio generation</li>\n<li>Reinforcement learning for large language models and diffusion models</li>\n<li>End-to-end system optimization, from performance benchmarking to kernel optimization</li>\n<li>GPUs, Kubernetes, PyTorch, or distributed training infrastructure</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Training state-of-the art neural audio codecs for 48 kHz stereo audio</li>\n<li>Developing novel algorithms for diffusion pretraining and reinforcement learning</li>\n<li>Scaling audio datasets to millions of hours of high quality audio</li>\n<li>Creating robust evaluation methodologies for hard-to-measure qualities such as naturalness or expressiveness</li>\n<li>Studying training dynamics of mixed audio-text language models</li>\n<li>Optimizing latency and inference throughput for deployed streaming audio systems</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> 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.</p>\n<p><strong>Visa sponsorship:</strong> 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.</p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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> 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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Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 55,000 businesses. If you are an expert in post-training Diffusion models for generative AI, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Apply DPO (direct preference optimisation) to pre-trained models.</li>\n<li>Adapt models to extend their capabilities, for instance, by changing conditioning inputs.</li>\n<li>Build solutions for dubbing and evaluate the quality of lip-sync.</li>\n<li>Implement post-training optimization techniques, such as quantization, pruning and distillation, to improve the efficiency of diffusion models used in avatar generation.</li>\n<li>Analyze and address challenges related to model performance, ensuring high-quality output in avatar rendering.</li>\n<li>Stay updated with the latest research and advancements in diffusion models, adversarial networks and post-training optimization methods.</li>\n</ul>\n<p><strong>What we&#39;re looking for:</strong></p>\n<ul>\n<li>You have a background in Computer Vision / Computer Science and 3+ years of industry experience.</li>\n<li>You have knowledge of recent advancements in post-training techniques. (for instance distillation, adversarial networks and efficient attention)</li>\n<li>You have worked with generative models for images and/or videos (Diffusion/GAN) preferably in the avatar domain.</li>\n<li>You are interested in doing research, trying new things and pushing the boundaries, going beyond what’s already known.</li>\n<li>You have experience in using most modern frameworks for machine learning and deep learning.</li>\n<li>You have great coding skills in Python and you care about writing clean code.</li>\n<li>You have experience with SDLC tools (Git), preferably CI/CD</li>\n</ul>\n<p><strong>Why join us?</strong></p>\n<p>We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why,</p>\n<p><strong>Our culture</strong></p>\n<p>At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here.</p>\n<p><strong>Serving 50,000+ customers (and 50% of the Fortune 500)</strong></p>\n<p>We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2.</p>\n<p><strong>Proprietary AI technology</strong></p>\n<p>Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind.</p>\n<p><strong>AI Safety, Ethics and Security</strong></p>\n<p>AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence&#39;s impact on our society is still unfolding, our position is clear: <strong>People first. 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