Research Engineer - LLM/VLM Inference Optimization (Seed Infra) Seattle Regular

ByteDance; Seattle (WA); On-site; USD 232,560 - 427,500; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) savings plan with company match

Paid parental leave

Generous paid holidays and sick days

Job summary

ByteDance is seeking a Research Engineer - LLM/VLM Inference Optimization in Seattle. The role involves designing and optimizing high-performance inference systems for large-scale LLMs and VLMs, requiring expertise in C/C++ and Python, and familiarity with GPU optimization techniques.

Ideal candidates will have a Bachelor's degree in Computer Science or related fields and experience in production-level inference systems. Benefits include competitive salaries, comprehensive health insurance, and generous paid time off.

Qualifications

• Bachelor's degree or above in Computer Science, Electrical Engineering, or related.
• Strong proficiency in C/C++ and Python.
• Experience deploying LLM/VLM inference at production scale.
• Familiarity with GPU architecture.
• Experience with performance optimization.

Responsibilities

• Design and optimize high-performance inference systems for large-scale LLMs and VLMs.
• Build model inference engines using advanced optimization techniques.
• Collaborate with research teams to identify performance issues.

Skills

C/C++ programming

Python

Algorithms and data structures

Machine learning frameworks (e.g., PyTorch, TensorFlow)

GPU architecture optimization

Education

Bachelor's degree in Computer Science or related field

Tools

CUDA

TensorRT

Triton

Job description

Research Engineer - LLM/VLM Inference Optimization (Seed Infra)

Location: Seattle

Team: Technology

Employment Type: Regular

Job Code: A236224

Responsibilities

• Design, develop, and optimize high-performance inference systems for large-scale LLMs and VLMs, covering inference engines, serving frameworks, and end‑to‑end deployment pipelines.
• Build state-of-the-art model inference engines through advanced performance optimization techniques such as compiler-level optimizations, parallel computing, graph fusion, efficient CUDA kernel development, low‑precision computation, streaming inference, speculative decoding, and high‑concurrency request optimization.
• Collaborate closely with other research teams to identify performance bottlenecks, conduct in-depth performance analysis, and optimize large models; contribute to the development of model toolchains and the broader technical ecosystem.

Minimum Qualifications

• Bachelor's degree or above in Computer Science, Electrical Engineering, Software Engineering, or a related field.
• Strong proficiency in C/C++ and Python; solid foundations in algorithms, data structures, and systems programming; familiarity with containerization and server-side debugging.
• Hands‑on experience with at least one mainstream machine learning framework (e.g., PyTorch, TensorFlow).
• Experience deploying or optimizing LLM/VLM inference at production scale, with demonstrated impact on latency, throughput, or serving cost.
• Familiarity with GPU architecture and experience optimizing compute‑intensive operators (e.g., FlashAttention, GEMM, GEMV, Conv2D).

Preferred Qualifications

• Experience with large-scale LLM serving infrastructure or equivalent production LLM deployment experience.
• Experience in GPU programming (CUDA/OpenCL) and familiarity with frameworks such as TensorRT, Triton, or CUTLASS.
• Experience in performance modeling, profiling, and optimization, or strong knowledge of CPU/GPU architectures.
• Familiarity with model/data parallelism frameworks for distributed inference.

Compensation & Benefits

The base salary range for this position in the selected city is $232,560 - $427,500 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.

Employees receive 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. 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).

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;
3. Exercising sound judgment.