Multimodal Vision & Evaluation ML Engineer Intern

ByteDance; Seattle (WA); On-site; USD 36,000 - 59,000; Part time

Benefits offered by this job

Health insurance

Housing allowance

10 paid holidays per year

Job summary

ByteDance’s Applied Machine Learning Ark team develops LLM MaaS platforms, spanning text and multimodal models, training, inference, and intelligent agents. The US team drives design, development, and operation across the US and international markets outside mainland China.

The campus intern role focuses on building evaluation systems, metrics, and video-enabled agents, with hands-on work in Python and PyTorch within a fast-moving AI research environment.

Qualifications

• Currently pursuing a degree aligned with Computer Science, AI, ML, CV or related field.
• Solid foundation in deep learning and computer vision, including generative modeling fundamentals.
• Demonstrated research or engineering ability through publications, projects, internships, or open-source work.

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

Python

Deep learning

Computer vision

Research experience

Education

Bachelor's degree in Computer Science, AI, ML, CV, or related field

Tools

PyTorch

Job description

ByteDance’s Applied Machine Learning Ark team develops LLM MaaS platforms, spanning text and multimodal models, training, inference, and intelligent agents. The US team drives design, development, and operation across the US and international markets outside mainland China.

The campus intern role focuses on building evaluation systems, metrics, and video-enabled agents, with hands-on work in Python and PyTorch within a fast-moving AI research environment.