Machine Learning Engineer - E-commerce Merchant Growth (LLM & Agentic Systems)

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Описание

About Us Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. Why Join ByteDance Inspiring creativity is at the core of ByteDance's mission. Our innovative products are 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 enrich life - a mission we work towards every day. As ByteDancers, 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. 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 & Inclusion ByteDance 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 ByteDance, our mission is to inspire creativity and enrich life. 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. About Our Team We’re the core team building LLM-powered agentic systems that drive and accelerate seller growth across global markets. We bring cutting-edge AI into production at scale — from applied LLMs and multi-agent systems to real-world business impact in one of the fastest-growing e-commerce ecosystems in the world. We’re looking for brilliant and motivated ML engineers eager to apply their knowledge in machine learning (ML), operations research (OR), data mining, and large-scale intelligent systems to real-world challenges. If you love building, experimenting, and shaping how AI transforms commerce, we want to talk to you. Applications are reviewed on a rolling basis — we encourage you to apply early. Responsibilities 1. Develop and deploy deep learning and LLM-powered systems for merchant operational tools and global e-commerce growth scenarios. 2. Leverage large-scale e-commerce data to power agentic systems that generate actionable insights — from CRM content generation and store decoration to automated email reply and outreach optimization. 3. , campaign design, pricing, and promotions). 4. ). 5. Build lead-scoring models, merchant tiering algorithms, outreach optimization systems, and knowledge graphs to enhance onboarding and retention efficiency. 6. Apply data mining and predictive modeling to optimize product pricing, promotion, and traffic allocation strategies. 7. Communicate technical insights effectively to both technical and non-technical stakeholders, fostering a collaborative, data-driven culture. Minimum Qualifications 1. Bachelor degree and above in Computer Science, Artificial Intelligence, Statistics, Operations Research, or related fields, with experience in data mining or deep learning. 2. Solid understanding of ML and deep learning fundamentals — classification, regression, NLP, and model optimization. 3. , PyTorch, TensorFlow). 4. Demonstrated ability to connect algorithms with business impact; highly self-driven with strong ownership and curiosity. 5. 2+ years of experience as an ML Engineer, ideally in NLP, recommendation, marketing, or growth algorithms. 6. Excellent analytical, teamwork, and communication skills. Preferred Qualifications 1. Experience in applied LLMs, multi-agent systems, or RAG (retrieval-augmented generation) pipelines. 2. ) or success in ML competitions. 3. Hands-on experience in e-commerce or other large-scale, data-intensive production environments. 4. Passion for building agentic systems that drive real-world business outcomes.

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