Machine Learning Engineer
12 hours ago
About TikTokTikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.Why Join UsInspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.Diversity & InclusionTikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.Job highlightsPositive team atmosphere, Career growth opportunity, 100+ mil users, Meal allowance, Competitive compensationResponsibilitiesAbout the teamThe Search Ranking Team is the core algorithm team of TikTok Search business. We are responsible for optimizing user experience in the search and recommendation scenario. We have opened full-link algorithm positions such as indexing, recall, rough sorting, fine sorting, rerank, and mix-rank. Here you'll have the opportunity to build a full-stack search engine system based on advanced AI methods to provide a world leading search engine. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.Responsibilities1. Using cutting-edge information retrieval and machine learning technologies, develop industry-leading search and recommendation algorithms that directly enhance the real experience of billions of global users. Here, you will have the opportunity to work on numerous advanced challenges such as optimizing trillion-scale index libraries, models with trillions of parameters, ultra-long user sequence modeling, and large-scale sparse models.2. Deeply explore how large-scale models will disrupt the next generation of search, recommendation, and ranking models, fully leveraging the world knowledge embedded in these models to bring revolutionary transformations to search and recommendation services. Here, you will have the opportunity to work with the industry's most cutting-edge technologies such as short-video multimodal understanding, generative models, scaling laws, sparse MoE, and reinforcement learning, harnessing massive computational power to become a highly sought-after talent3. Combine your understanding of product objectives and take full advantage of modern machine learning, AI, NLP/CV techniques to improve the search ranking algorithms, including query understanding, video understanding and various levels of result ranking.QualificationsMinimum Qualifications1. Bachelor degree or above in the field of computer science or a related technical discipline2. Proficient coding skills and strong algorithm & data structure using C++/Python/Java3. Have a solid knowledge of machine learning and practical experience in applying itPreferred Qualifications1. Effective communication and teamwork skills.2. Modeling experience in one or more of the following areas: Ads, Search engine, Recommender System, NLP/CV
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