Applied Scientist - LLM Training System as a Service - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

Bytedance; San Jose (CA); On-site; USD 218,000 - 480,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Paid parental leave

Disability coverage

Life insurance

Wellbeing benefits

Holidays and PTO

Job summary

ByteDance seeks a PhD candidate to join AML-MLsys to advance LLM training and inference, RL components, and scalable distributed systems. The role emphasizes building high-performance pipelines across global workloads.

You will collaborate with researchers to push the frontier of LLM/Agent training, optimize GPU/CUDA performance, and contribute to a robust, scalable ML infra used by billions of interactions daily.

Qualifications

• Pursuing a PhD in a technical discipline with strong CS fundamentals.
• Strong knowledge of algorithms and data structures; proficient in Python.
• Understanding of deep learning, neural networks and DL training frameworks (e.g., PyTorch).

Responsibilities

• Develop and optimize LLM training, inference, and RL frameworks.
• Collaborate with model researchers to scale LLM training and RL.
• Optimize GPU/CUDA performance for high‑throughput LLM systems.

Skills

Algorithms and data structures

Python

Education

PhD in computer science / automation / electronics engineering or related

Tools

CUDA

FSDP

Deepspeed

JAX SPMD

Megatron-LM

Verl

TensorRT-LLM

ORCA

VLLM

SGLang

Job description

Responsibilities

We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.

Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.

Team Introduction

AML-MLsys combines system engineering and the art of machine learning to develop and maintain massively distributed ML training and Inference system/services around the world, providing high-performance, highly reliable, scalable systems for LLM/AIGC/AGI.

Topic Content

With the evolution from large language models (LLMs) to AI Agents, the training paradigm is undergoing a fundamental shift. Traditional distributed training frameworks like Megatron-LM are designed around relatively static parallelism strategies, whereas Agent training introduces more dynamic patterns, including external tool interactions, multi-step reasoning, and iterative self-improvement.

In this context, tightly coupled system design can limit flexibility and efficiency. To better support these emerging workloads, we aim to build a robust architecture that cleanly separates "logical control" from "compute execution," enabling more scalable and adaptable training workflows.

Responsibilities

• Responsible for developing and optimizing LLM training & inference & Reinforcement Learning framework.
• Working closely with model researchers to scale LLM training & Reinforcement Learning to the next level.
• Responsible for GPU and CUDA Performance optimization to create an industry-leading high-performance LLM training and inference and RL engine.

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD in computer science, automation, electronics engineering or a related technical discipline
• Proficient in algorithms and data structures, familiar with Python
• Understand the basic principles of deep learning algorithms, be familiar with the basic architecture of neural networks and understand deep learning training frameworks such as Pytorch.

Preferred Qualifications

• Proficient in GPU high-performance computing optimization technology on CUDA, in-depth understanding of computer architecture, familiar with parallel computing optimization, memory access optimization, low-bit computing, etc.
• Familiar with FSDP, Deepspeed, JAX SPMD, Megatron-LM, Verl, TensorRT-LLM, ORCA, VLLM, SGLang, etc.
• Knowledge of LLM models, experience in accelerating LLM model optimization is preferred.

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $218400 - $480000 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.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

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:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
• Exercising sound judgment.

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.

Reasonable Accommodation

ByteDance 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://tinyurl.com/RA-request