Visual Generation & Multimodal Evaluation Machine Learning Engineer Graduate (AML-Ark-US) - 2027 Start

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of products including TikTok, Lemon8, CapCut, Pico, 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, offering businesses Model-as-a-Service (MaaS) solutions globally, excluding mainland China.

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.
• Operate large-scale log analytics pipelines processing invocation logs from text models, multimodal models, and agent systems to extract usage patterns, quality signals, and actionable insights.
• Drive the design, development, and operation of MaaS solutions, spanning text and multimodal LLM algorithms, training/fine-tuning/inference frameworks, prompt engineering, model alignment, and intelligent agent systems.

Qualifications

Minimum Qualifications

• Completing or recently completed a Bachelor's/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 medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave, short-term and long-term disability coverage, and life insurance.
• Wellbeing benefits.
• 10 paid holidays per year, 10 paid sick days per year, and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

Pay

The base salary range for this position is $128,000 - $256,000 annually. Compensation may vary based on qualifications, skills, competencies, experience, and location. This role may also be eligible for additional discretionary bonuses/incentives and restricted stock units.