Researcher - Large Language Models, AML

earning Enterprise team combines system engineering and machine learning to develop and operate Large Language Model (LLM) service platform that offers businesses Model-as-a-Service solutions (MaaS) to both the big model vendors and users. The Applied Machine Learning Enterprise US team drives the design, development, and operation of MaaS solutions in US and rest of world overseas of mainland China. We are building full stack end-to-end solutions covering text and multi-modality LLM algorithms, LLM training/finetuning/inference frameworks, heterogeneous hardware architectures, prompting engineering, LLM model alignment, and intelligent agents, etc. We are actively seeking talented Researcher/Scientist specializing in Large Language Models (LLM) to join our dynamic team.

In this role, you will be at the forefront of cutting-edge research and development of advanced techniques for LLM solutions including model fine-tuning, evaluation, inference, alignment, prompt engineering, intelligent agent, etc. To ensure we have the ability to run current and future models at increasingly high scale with unprecedented efficiency.

Your main responsibilities will be

• lead the creation of next-generation, high-capacity LLM platforms and innovative products.
• work closely with cross-functional teams to plan and implement projects harnessing LLMs for diverse purposes and vertical domains.
• maintain a deep passion for contributing to the success of large models is essential in this innovative and fast-paced team environment.

Qualifications

Minimum Qualification

• Ph.D./Master in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, active learning, alignment research, agent ecosystem, etc.) and possess practical expertise in effectively implementing these advanced systems.
• Proficiency in programming languages such as Python, Rust, or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, megatron, vllm, etc.).
• Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference. Being familiar with PEFT, RL, MoE, CoT or Langchain is a plus.

Preferred Qualification

• Excellent problem-solving skills and a creative mindset to address complex AI challenges. Demonstrated ability to drive research projects from idea to implementation, producing tangible outcomes.
• Published research papers or contributions to the LLM community would be a significant plus.
• Experience with inference tuning and Inference acceleration. Have a deep understanding of GPU and/or other AI accelerators, experience with large scale AI networks, pytorch 2.0 and similar technologies.
• Experience with large scale machine learning systems' scheduling and orchestration, familiar with Kubernetes and Docker.
• Experience with evaluation of AI systems, LLM application & agent development is desirable.

TikTok 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 [email protected]

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $145000 - $355000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:

We cover 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents and offer a Health Savings Account(HSA) with a company match. As well as Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans. In addition to Flexible Spending Account(FSA) Options like Health Care, Limited Purpose and Dependent Care.

Our time off and leave plans are: 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.

We also provide generous benefits like mental and emotional health benefits through our EAP and Lyra. A 401K company match, gym and cellphone service reimbursements. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.