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

ByteDance’s Applied Machine Learning Ark team builds and operates Large Language Model (LLM) service platforms that deliver Model-as-a-Service (MaaS) solutions to both model providers and enterprise users. The US team designs, develops, and runs full-stack, end-to-end MaaS solutions—spanning text and multimodal LLM algorithms, training/fine-tuning/inference frameworks, prompt engineering, model alignment, and intelligent agent systems—across the US and international markets outside mainland China. In addition to model serving, the team operates large-scale log analytics pipelines that process invocation logs from text, multimodal, and agent systems to extract usage patterns, quality signals, and actionable insights that drive model improvement, system optimization, and product decisions.

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.

Requirements

• Bachelor’s or Master’s degree (completed or near completion) 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 a multimodal evaluation framework.
• Demonstrated research or engineering ability through publications, substantial projects, internships, or open-source work.

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 medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short-term and long-term disability coverage, life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
• Additional discretionary bonuses/incentives and restricted stock units may be available for this role.

Pay

Base salary range for this position is $121,600 – $243,200 annually, depending on qualifications, skills, experience, and location.