Machine Learning Engineer, Supply Chain Forecasting

Location
D01 Marina, Raffles Place, People's Park, Cecil
Job Type
Full-time
Experience
Mid
Category
General
Salary
$11,250 - $22,500
Posted
1 day ago
Expires
Jul 31, 2026
Views
1

Job Details

Vacancies

1 position

Experience Required

No experience required

Job Description

About Us

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

Why Join ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

About Our Team

Our team is missioned for the research, development, and implementation of algorithms for core supply chain scenarios. Focus on building intelligent decision-making solutions for the supply chain based on large models, encompassing core operations such as sales forecasting, replenishment planning, capacity planning, and inventory allocation. Simultaneously, explore the application of algorithmic technologies in more business areas to ensure the effectiveness of algorithm implementation and deliver business value.

Job Responsibilities

1. Lead the research, development, implementation, and iterative improvement of algorithms related to multi-scenario supply chain forecasting, replenishment, capacity, and allocation.

2. Apply large model technologies to business scenarios, demonstrating proficiency in the design and practical implementation of key techniques including Pre-training (PT), Continuous Pre-training (CPT), Supervised Fine-Tuning (SFT), Reinforcement Learning (RL), and AI Agents.

3. Possess an application-oriented mindset, collaborate with business teams to realize the value of algorithms, and continuously explore new opportunities to enhance operational efficiency and manpower productivity.

Minimum Qualifications

1. Bachelor's degree or higher in Computer Science, Mathematics, Artificial Intelligence, or related fields. Solid foundational knowledge of machine learning and hands-on experience with algorithms in real-world business scenarios are required.

2. Expert in the practical application of large models in the industry, with proven experience in SFT, RL, and Agents. Familiarity with training frameworks like LLaMA Factory is essential.

3. Proficient in Python and deep learning frameworks such as PyTorch or TensorFlow. Strong problem-solving skills are a must.

4. Strong sense of responsibility and a commitment to continuous learning, with the ability to stay abreast of cutting-edge large model technologies and apply them to business problems.

Preferred Qualifications

1. Published work in top-tier conferences (KDD, NeurIPS, ICML, SIGIR, WSDM, WWW, AAAI, IJCAI, RecSys, etc.) or success in ML competitions.

2. Passion for building agentic systems that drive real-world business outcomes.

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