Visual Generation & Multimodal Evaluation Machine Learning Engineer Intern (AML-Ark-US) - 2027 Summer

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of products including TikTok, Lemon8, CapCut, and Pico, as well as platforms specific to the China market like Toutiao, Douyin, and Xigua, ByteDance makes it easier and more fun for people to connect with, consume, and create content.

The Applied Machine Learning Ark team combines system engineering and machine learning to develop and operate Large Language Model (LLM) service platforms that offer businesses Model-as-a-Service (MaaS) solutions, serving both large model providers and downstream users. The US team drives the design, development, and operation of MaaS solutions across the US and international markets outside mainland China. We build full-stack, end-to-end solutions spanning text and multimodal LLM algorithms, training/fine-tuning/inference frameworks, prompt engineering, model alignment, and intelligent agent systems. Beyond model serving, we operate large-scale log analytics pipelines processing massive volumes of invocation logs to extract usage patterns, quality signals, and actionable insights for model improvement and system optimization.

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.

Qualifications

Minimum Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a related field.
• Solid foundation in deep learning and computer vision, including generative modeling fundamentals.
• Practical experience in at least one of: visual generation, multimodal LLMs, video understanding, or visual quality assessment.
• Strong Python skills and proficiency with PyTorch or an equivalent framework, or multimodal evaluation framework.
• Demonstrated research or engineering ability through publications, substantial projects, internships, or open-source work.

Preferred Qualifications

• Publications at top-tier vision or ML venues (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
• Hands-on experience with modern visual generation stacks, including diffusion-based models and their post-training.
• Familiarity with visual generation benchmarks, or experience building evaluation frameworks.
• Experience applying agent frameworks to creative workflows, or working with large-scale video data infrastructure.

Benefits

• Day one access to health insurance, life insurance, and wellbeing benefits.
• 10 paid holidays per year and paid sick time (56 hours if hired in the first half of the year, 40 if hired in the second half).
• Eligibility for housing allowance if not working 100% remote.

Pay

The hourly rate range for this position is $42.75.