Research Intern (AML) - 2026 Start (PhD)

关于这个机会

You will be joining our Applied Machine Learning team, a central team responsible for delivering state-of-the-art solutions powering our company's recommendations, ads, and search systems across various products such as TikTok, Douyin. We own the end-to-end ML lifecycle, from ideation and research to building, deploying, and iterating on models in production. We are looking for candidates who are passionate about solving complex problems and have a strong foundation in machine learning theory and practice. We are looking for talented individuals to join us for an internship in 2026. PhD Internships at ByteDance aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. PhD internships at ByteDance provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date). Responsibilities: 1. Responsible for the construction and operations & maintenance (O&M) of the centralized GPU computing pool, generating additional AI computing capacity through more optimized resource scheduling strategies. 2. Responsible for the collection, processing, and mining of GPU data across the entire Group; leveraging data-driven insights to effectively manage overall Group-wide GPU resources, including budgeting, delivery, resource efficiency optimization, and secondary utilization (reuse).

任职要求

Minimum Qualifications: 1. Currently pursuing an PhD in Computer Science or a related fields. 2. Proficiency in at least one programming language among Python, Golang, or C++, with good coding practices and solid programming skills. 3. Proficient in common storage and middleware systems (such as MySQL, Redis, and MQ), with practical troubleshooting and performance tuning capabilities. 4. Familiar with common time-series data components (e.g., OpenTSDB, Prometheus, InfluxDB) and OLAP databases (e.g., ClickHouse). 5. Solid understanding of distributed system principles, with hands-on experience in the design, development, and maintenance of large-scale distributed systems. 6. Strong sense of responsibility, excellent learning and communication skills, highly self-motivated, and a good team player.

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