Tech Lead, Machine Learning Engineer, Foundation Model Applications

$172,000 - $337,280/Yr

Tiktok - San Jose, CA

Full-time - Mid Level

San Jose, CA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. As a Tech Lead in the Machine Learning Engineer team focusing on Foundation Model Applications, you will be part of a pioneering group committed to leveraging cutting-edge technologies to enhance TikTok's user experience. Our team culture is built around the "First Principles Thinking" approach, which emphasizes understanding the core of problems and delivering well-grounded solutions. In this role, you will be responsible for understanding and optimizing TikTok's industry-leading recommendation system. You will deploy, prompt, and fine-tune advanced foundation models to improve our recommendation system and product offerings, ultimately enhancing the experience for billions of consumers and creators. Collaboration is key; you will work closely with cross-functional teams, including product managers, data scientists, and product engineers, to identify and solve problems, refine machine learning algorithms, and communicate results effectively. Regular A/B testing, performance analysis, and algorithm iteration will be part of your routine, as well as working with infrastructure teams to enhance the efficiency and stability of our machine learning systems.

Responsibilities

• Understand and optimize TikTok's industry-leading recommendation system
• Deploy, prompt, and fine-tune cutting-edge foundation models
• Apply foundation models to enhance TikTok's recommendation system and product offerings
• Collaborate with cross-functional teams to solve problems and refine machine learning algorithms
• Regularly run A/B tests, perform analyses, and iterate algorithms based on results
• Work with infrastructure teams on improving the efficiency and stability of machine learning systems

Requirements

• Hands-on experience in Machine Learning, Deep Learning, Recommender Systems, Data Mining, Natural Language Processing, or Computer Vision
• Strong programming skills in Python and/or C/C++
• Deep understanding of data structures and algorithms
• Familiarity with at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet)
• Excellent communication and teamwork skills
• Passion for learning new techniques and tackling challenging problems

Nice-to-haves

• Prior research/industry experience with deploying, prompting, and fine-tuning foundation models
• Prior research/industry experience with applied machine learning or large-scale recommendation systems
• Publications at major AI-related conferences such as NeurIPS, ICML, ICLR, AAAI, IJCAI, ACL, NAACL, EMNLP, CVPR, ICCV, ECCV, KDD, ICDM, SDM, RecSys
• Strong track record in AI-related competitions or participation in high visibility public/open-source AI-related projects
• A strong passion for First Principles Thinking

Benefits

• 100% premium coverage for employee medical insurance
• Approximately 75% premium coverage for dependents
• Health Savings Account (HSA) with company match
• Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans
• Flexible Spending Account (FSA) options for healthcare and dependent care
• 10 paid holidays per year
• 17 days of Paid Personal Time Off (PPTO)
• 10 paid sick days per year
• 12 weeks of paid Parental leave
• 8 weeks of paid Supplemental Disability
• Mental and emotional health benefits through EAP and Lyra
• 401K company match
• Gym and cellphone service reimbursements