Job
LLM Software Engineer/Researcher Graduate (Applied Machine Learning) - 2024 Start (PhD)
ByteDance
•
Nov 28
💼 Graduate Job
San Jose
AI generated summary
- The candidate must have a Ph.D./Master's degree in Computer Science or related field, prior experience with large language models, practical expertise in implementing advanced systems, proficiency in Python/C++, familiarity with deep learning frameworks, and knowledge of distributed computing framework and performance tuning. Publications in the LLM community, experience with GPU/ AI accelerators and large scale machine learning systems, as well as deployment and testing of AI models are preferred qualifications.
- The candidate will lead the development of advanced techniques for MaaS solutions, collaborate with cross-functional teams on LLM projects, and contribute to the success of large models in a fast-paced environment.
Description
- The Applied Machine Learning Enterprise team combines system engineering and machine learning to develop and operate big model service platform that offers businesses Model-as-a-Service solutions (MaaS) to both the big model vendors and users. We are actively seeking talented Software Engineers/Researchers specializing in Large Language Models (LLM) to join our dynamic team
- We are looking for talented individuals to join our team in 2024. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with ByteDance.
Requirements
- Ph.D./Master in Computer Science, Artificial Intelligence, or a related field.
- Have prior experience working with training and inference of large language models.
- Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, alignment research etc.) and possess practical expertise in effectively implementing these advanced systems.
- Proficiency in programming languages such as Python or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, etc.).
- Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference. Being familiar with PEFT or MoE is a plus.
- Preferred Qualifications:
- 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 Cloud Native technologies.
- Experience with deploying AI models into production environments, testing and evaluation of AI systems, LLM application & agent development is desirable.
Education requirements
Masters
PhD
Area of Responsibilities
Software Engineering
Data
Responsibilities
- In this role, you will be at the forefront of cutting-edge research and development of advanced techniques for MaaS solutions including model continuous pretraining, fine-tuning, evaluation, inference capabilities and also LLM application/agent development. Your primary responsibility will be to:
- 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.
Details
Work type
Full time
Work mode
office
Location
San Jose