Machine Learning Engineer Graduate (TikTok Recommendation) - 2024 Start (BS/MS)
- San Jose, CA
- Permanent
- Full-time
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.About the Team
Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.Responsibilities - What You'II Do
- Build industry-leading recommendation system, improving user experience, content ecosystem and platform security;
- Deliver end-to-end machine learning solution to address critical product challenges;
- Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.
- Work with cross functional teams to design product strategies and build solutions to grow TikTok in important markets.We are looking for talented individuals to join our team in 2024. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.Successful candidates must be able to commit to one of the following start dates below:
1. January 15, 2024
2. February 5, 2024
3. March 4, 2024
4. May 20, 2024
5. June 10, 2024
6. July 15, 2024
7. August 12, 2024
We will prioritize candidates who are able to commit to these start dates. Please state your availability and graduation date clearly in your resume.Applications will be reviewed on a rolling basis. We encourage you to apply early.Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.Qualifications:Minimum Qualifications
- Bachelor degree or above in the field of computer science or a related technical discipline
- Proficient coding skills and strong algorithm & data structure using C++/Python or other programming language
- Experienced in Machine Learning, familiar with at least one DeepLearning framework, e.g. PyTorch, Tensorflow.
- Effective communication and teamwork skillsPreferred Qualifications
- Experienced in one or more of the following areas, e.g. NLP, CV, Recommender System, and Machine Learning, etc
- Authors of published papers in top academia conferences is an advantage
- Winners of algorithm and machine learning competitions such as ACM and Kaggle is an advantageTikTok 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.TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://shorturl.at/cdpT2By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy.