Multimodal Vision & AI Evaluation Researcher

Bytedance; San Jose (CA); Hybrid; USD 150,000 - 230,000; Full time

Job summary

ByteDance seeks engineers and researchers to advance Large Language Models and AI agents within the Applied Machine Learning Ark. The US team coordinates design, development, and operation of MaaS solutions across the US and international markets outside China.

You will work on end-to-end, full-stack solutions spanning text and multimodal LLMs, training, inference, and intelligent agent systems, with opportunities to pursue bold ideas and impactful research.

Qualifications

• PhD student or recent PhD in CS/AI/ML/CV.
• Strong foundation in deep learning and computer vision, including generative modeling fundamentals.
• Experience in visual generation, multimodal LLMs, video understanding, or visual quality assessment.
• Strong Python skills and PyTorch or equivalent framework.
• Demonstrated research or engineering ability through publications, projects, internships, or OSS.

Responsibilities

• Build evaluation systems for image and video models/agents, covering generation quality, instruction following, multimodal understanding, and safety.
• Develop automated metrics and model-based evaluators, and design reproducible human evaluation protocols.
• Design and develop video generation/debugging agents that orchestrate multi-step creative workflows.
• Build large-scale image and video data pipelines, and turn evaluation findings into model and product improvements.

Skills

PhD in CS/AI/ML/CV

Deep learning

Computer vision

Python

PyTorch

Research/engineering ability

Education

PhD (completed or near completion) in CS/AI/ML/CV

Tools

PyTorch

Multimodal evaluation framework

Job description

ByteDance seeks engineers and researchers to advance Large Language Models and AI agents within the Applied Machine Learning Ark. The US team coordinates design, development, and operation of MaaS solutions across the US and international markets outside China.

You will work on end-to-end, full-stack solutions spanning text and multimodal LLMs, training, inference, and intelligent agent systems, with opportunities to pursue bold ideas and impactful research.