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Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. The Team The Studio Media Algorithms team is at the forefront of algorithmic innovation to enhance and support the creation of Netflix's entertainment content, including games. In this role, you will be embedded within this team while collaborating very closely with a specialized Games Studio R&D team. This incubation-style team is chartered to lead our investments in building new kinds of games leveraging emerging technologies to support our creators and reach player audiences in new ways. The Role We are seeking a Machine Learning Scientist to lead the research and development of Large Language Models (LLMs), Vision-Language Models (VLMs), and multi-modal foundations and solutions for games. This role is defined by a mandate for inference efficiency ; you will not only build and fine-tune state-of-the-art models but also lead the algorithmic innovation required to make them viable in terms of cost, latency, and quality across a variety of cloud and edge devices. 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We are looking for an outstanding machine learning engineer to join our team! The role will provide an opportunity to work on large scale machine learning to improve the podcast creation experience at Zencastr. You'll join a team of hardworking engineers that are passionate about understanding what drives users' long-term happiness with Zencastr, and how our recommendations and content affects that. As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers in prototyping and productizing brand-new ML at the intersection of speech processing and long-term user satisfaction. 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Containerization for goods. SWIFT for money. Stripe for payments. Compliance is one of the last and largest - and the hardest, because trade rules aren't data to be looked up. They're a complex adaptive system with 190+ sovereign jurisdictions, in different languages, changing constantly, reacting to each other. Sphere built the system that solves it. Our AI (TRAM) ingests global trade law, interprets it, resolves conflicts across jurisdictions, and produces compliance determinations more reliable than human experts. We handle the entire lifecycle - calculation, registration, filing, remittance - at millisecond latency with zero downtime. - Backed by a16z and YC. $21M Series A, 30%+ month-over-month growth, customers include ElevenLabs, Replit, Deel, Runway, and Lovable. - Small team, global surface area. Everyone owns a domain that would be a full team at a larger company. San Francisco, five days in office. - The problem keeps compounding. 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