Software Engineer in ML Systems Graduate (AML - Machine Learning Systems) - 2026 Start (BS/MS)

Responsibilities

We are looking for talented individuals to join our team in 2026. 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 ByteDance.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

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 ByteDance and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

What You'll Do
The AML Machine Learning Systems team provides E2E machine learning experience and machine learning resources for the company. The team builds heterogeneous ML training and inference systems based on GPU and AI chips and advances the state-of-the-art of ML systems technology to accelerate models such as stable diffusion and LLM. The team is also responsible for research and development of hardware acceleration technologies for AI and cloud computing, via technologies such as distributed systems, compilers, HPC, and RDMA networking. The team is reinventing the ML infra for large scale language models. We have published papers at top tier conferences such as SIGCOMM, NSDI, EuroSys, OSDI, SOSP, MLSys, NeurIPS, etc.

Responsibilities
- Research and develop our machine learning systems, including heterogeneous computing architecture, management, and monitoring
- Deploy machine learning systems, distributed task scheduling, machine learning training
- Manage cross-layer optimization of system and AI algorithms and hardware for machine learning (GPU, ASIC)
- Implement both general purpose training framework features and model specific optimizations (e.g. LLM, diffusions)
- Improve efficiency and stability for extremely large scale distributed training jobs

Qualifications

Minimum Qualifications
1. Master distributed, parallel computing principles; know the recent advances in computing, storage, networking, and hardware technologies;
2. Familiar with machine learning algorithms, platforms and frameworks such as PyTorch and Jax;
3. Have basic understanding of how GPU and/or ASIC works;
4. Expert in at least one or two programming languages in Linux environment: C/C++, CUDA, Python.

Preferred Qualifications
- GPU based high performance computing, RDMA high performance network (MPI, NCCL, ibverbs);
-Distributed training framework optimizations such as DeepSpeed, FSDP, Megatron, GSPMD;
- AI compiler stacks such as torch.fx, XLA and MLIR;
- Large scale data processing and parallel computing;
- Experiences in designing and operating large scale systems in cloud computing or machine learning;
- Experiences in in-depth CUDA programming and performance tuning (cutlass, triton).

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Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $106590 - $139650 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 condit