AI Machine Learning Engineer Graduate (Search) - 2026 Start (PhD)

ByteDance; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

ByteDance in Singapore is seeking talented individuals for their Search Team, focused on developing cutting-edge software solutions including a full-stack search engine. The role requires PhD-level candidates with robust skills in C++, Python, Java, and a background in machine learning.

Successful applicants will engage in innovative projects, applying deep learning in real-world applications. Strong communication skills and a foundation in algorithms related to machine learning models are preferred. Join ByteDance and navigate the frontiers of technology.

Qualifications

• Completion of a PhD degree in a relevant technical discipline.
• Strong coding skills and knowledge of algorithms & data structures.
• Practical experience in applying machine learning.

Responsibilities

• Build a full-stack search engine system.
• Research and innovate in large-scale computing and machine learning technologies.
• Collaborate on cross-modal matching technologies.

Skills

C++

Python

Java

Machine Learning

Deep Learning

Data Structures

Algorithms

Education

PhD in Software Development, Computer Science, or related field

Job description

Responsibilities

Team Introduction

Our Search Team is responsible for building and owning our search engine which provides our users the best search experience. On the Search Team, you’ll have the opportunity to build a full‑stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, Computer Vision, Multimodal, and Recommender Systems. We embrace a culture of self‑direction, intellectual curiosity, openness, and problem‑solving.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

• Exploring Cutting‑Edge NLP Technologies: From basic tasks like word segmentation and Named Entity Recognition (NER) to advanced business functions like text and multimodal pre‑training, query analysis, and fundamental relevance modeling, we apply deep learning models throughout the pipeline where every detail presents a challenge.
• Cross‑Modal Matching Technologies: Applying deep learning techniques that combine Computer Vision (CV) and Natural Language Processing (NLP) in search, we aim to achieve powerful semantic understanding and retrieval capabilities for multimodal video search.
• Large‑Scale Streaming Machine Learning Technologies: Utilising large‑scale machine learning to address recommendation challenges in search, making the search more personalized and intuitive in understanding user needs.
• Architecture for data at the scale of hundreds of billions: Conducting in‑depth research and innovation in all aspects, from large‑scale offline computing and performance and scheduling optimization of distributed systems to building high‑availability, high‑throughput, and low‑latency online services.
• Recommendation Technologies: Leveraging ultra‑large‑scale machine learning to build industry‑leading search recommendation systems and continuously explore and innovate in search recommendation technologies.

Minimum Qualifications

• Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Proficient coding skills and strong algorithm & data structure using C++/Python/Java.
• Have a solid knowledge of machine learning and practical experience in applying it.

Preferred Qualifications

• Effective communication and teamwork skills.
• Modeling experience in one or more of the following areas: Ads, Search engine, Recommender System, NLP/CV.
• Have a solid foundation in algorithms related to LLMs, including but not limited to comprehensive learning and practical experience in areas such as single‑modal/multi‑modal LLM application and deployment.
• Strong publications record in top conferences or journals (e.g., ICLR, NeurIPS, ICML, ACL, EMNLP, NAACL, CVPR, ICCV and ECCV).