Software Engineer Graduate – Applied Machine Learning – Enterprise – PhD
Company | ByteDance |
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Location | San Jose, CA, USA |
Salary | $Not Provided – $Not Provided |
Type | Full-Time |
Degrees | PhD |
Experience Level | Entry Level/New Grad |
Requirements
- PhD in Computer Science, Artificial Intelligence, or a related field.
- Have prior experience working with training or inference of large language models.
- Strong understanding of cutting-edge LLM research (e.g., long context, multi modality, finetuning, alignment, RL, agent, 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 or agent frameworks.
Responsibilities
- 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.
- Design and develop AI agents for a wide range of AI native applications, including multi-modality (image/video/audio). Continuously improve the agent’s ability of understanding, reasoning, tool selection, taking actions at blazing fast speed.
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.
- Experience with building LLM Applications, have a deep understanding of Agentic frameworks, RAG, Test-time scaling, Reasoning, Evaluation, Multi-modality, etc.
- Experience with deploying AI applications into production environments, prompt optimizing, testing and evaluation of AI systems, LLM application & agent development is desirable.
- Experience or publications in multi-modal is a plus, including image/video/audio understanding, text-to-image, text-to-video, etc.