Multimodal ML Engineer: Visual Generation & Evaluation

ByteDance; San Jose (CA); On-site; USD 128,000 - 256,000; Full time

Job summary

ByteDance is seeking graduates to contribute to Applied Machine Learning Ark efforts, building MaaS platforms for LLM services and developing end-to-end systems spanning text and multimodal models. You will work on evaluation systems, large-scale data pipelines, and model improvements using state-of-the-art ML techniques in a dynamic, globally distributed team.

Successful candidates should have a strong foundation in deep learning, vision, and Python/PyTorch, with demonstrated research or

Qualifications

• Bachelor's/Master's in CS, AI, ML, CV or related field.
• Strong foundation in deep learning and computer vision, incl. generative modeling.
• Experience in visual generation, multimodal LLMs, video understanding, or visual quality assessment.
• Strong Python and PyTorch or similar framework.
• 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

Deep learning

Computer vision

Python

PyTorch

Research experience

Education

Bachelor's/Master's in CS/AI/ML/CV

Tools

Diffusion models

Video data pipelines

Job description

ByteDance is seeking graduates to contribute to Applied Machine Learning Ark efforts, building MaaS platforms for LLM services and developing end-to-end systems spanning text and multimodal models. You will work on evaluation systems, large-scale data pipelines, and model improvements using state-of-the-art ML techniques in a dynamic, globally distributed team.

Successful candidates should have a strong foundation in deep learning, vision, and Python/PyTorch, with demonstrated research or