Visual Generation & Multimodal Evaluation Scientist

ByteDance; San Jose (CA); On-site; USD 162,000 - 317,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid parental leave

Disability insurance

Life insurance

Wellbeing benefits

10 paid holidays per year

10 paid sick days per year

Paid Personal Time

Job summary

ByteDance is seeking engineers and researchers for the Applied Machine Learning Ark team to build and operate MaaS platforms spanning text and multimodal LLMs. You will help design, train, evaluate, and deploy end-to-end solutions, including model alignment, inference, and agent systems, while processing large volumes of logs for continuous improvement.

We welcome PhDs with deep learning and vision/multimodal experience, strong Python/PyTorch skills, and a track record of publications or

Qualifications

• PhD completed or near completion in CS/AI/ML, CV or related field.
• Strong foundation in deep learning and computer vision.
• Experience in visual generation, multimodal LLMs, video understanding, or visual quality assessment.
• Proficiency in Python and PyTorch or similar framework.
• Demonstrated research or engineering ability via publications, projects, internships, or open-source work.

Responsibilities

• Build evaluation systems for image and video models/agents.
• Develop automated metrics and evaluators; design reproducible human eval protocols.
• Design and develop video generation/debugging agents.
• Build large-scale image/video data pipelines; translate findings into model improvements.

Skills

Strong Python

PyTorch

Deep learning fundamentals

Vision/Multimodal ML

Research publications

Education

PhD in Computer Science / AI / ML / CV

Tools

Diffusion-based models

Large-scale video data infra

Job description

ByteDance is seeking engineers and researchers for the Applied Machine Learning Ark team to build and operate MaaS platforms spanning text and multimodal LLMs. You will help design, train, evaluate, and deploy end-to-end solutions, including model alignment, inference, and agent systems, while processing large volumes of logs for continuous improvement.

We welcome PhDs with deep learning and vision/multimodal experience, strong Python/PyTorch skills, and a track record of publications or