ByteDance

2 days ago

Machine Learning Engineer - Logistics Fulfillment

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 32 minutes agoStatus: Live

Job Summary

Build and deploy AI/operations research algorithms for global logistics and fulfillment. Implement deep reinforcement learning for in-warehouse decisions (order batching, wave picking, dynamic packaging), design first-mile/last-mile scheduling and routing, and advance middle-mile trunk transportation optimization. Contribute to global network planning using large-language-model-driven simulation, explore multimodal AI for warehouse scanning and traceability, and help productize algorithms with cross-functional partners.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Implement operations research and AI projects for self-owned and quasi-self-owned warehouse operations, including algorithm development and system implementation/iteration.
•Build reinforcement-learning-based algorithms for first-mile/last-mile decisions such as dynamic collection routes, merchant onboarding/offboarding, and regional division; improve delivery-station allocation and prediction models.
•Participate in global logistics backbone network planning by simulating complex supply chain scenarios with large language models and optimizing decision-making efficiency and scientific rigor.
•Develop middle-mile intelligent scheduling algorithms, including reinforcement learning for trunk-line dynamic routing and capacity scheduling.
•Advance AI innovation by applying multimodal large models for warehouse image recognition, missing-part identification, and automated traceability of abnormal scenarios; productize algorithms with cross-functional partners.

Key Requirements

•Bachelor’s degree or above in math, statistics, computer science, industrial engineering, supply chain/logistics, operations research, or related fields.
•Strong data structures and algorithm design foundation; proficiency in at least one programming language such as Python, Java, C++, or R.
•Expertise in deep learning and reinforcement learning (including sequence decision-making and multi-agent RL), operations research optimization (integer and stochastic programming), and large models (LLM fine-tuning, multimodal large models).
•Prefer logistics/supply-chain experience with relevant algorithm implementation.
•Strong learning ability, clear logic, teamwork and communication skills, and proficient English writing/communication.

Experience:LogisticsSupply chain

Education:Bachelor's

Skills:Learning abilityCuriosityClear logicTeamworkCommunication

Languages:English

Tech Stack:PythonJavaC++RData structuresAlgorithmsDeep learningReinforcement learningSequence decision-makingMulti-agent reinforcement learningOperations research optimizationInteger programmingStochastic programmingLarge modelsLLM application fine-tuningMultimodal large models

Company Brief

ByteDance

Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn

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ByteDance

2 days ago

Machine Learning Engineer - Logistics Fulfillment

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 32 minutes agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Implement operations research and AI projects for self-owned and quasi-self-owned warehouse operations, including algorithm development and system implementation/iteration.
•Build reinforcement-learning-based algorithms for first-mile/last-mile decisions such as dynamic collection routes, merchant onboarding/offboarding, and regional division; improve delivery-station allocation and prediction models.
•Participate in global logistics backbone network planning by simulating complex supply chain scenarios with large language models and optimizing decision-making efficiency and scientific rigor.
•Develop middle-mile intelligent scheduling algorithms, including reinforcement learning for trunk-line dynamic routing and capacity scheduling.
•Advance AI innovation by applying multimodal large models for warehouse image recognition, missing-part identification, and automated traceability of abnormal scenarios; productize algorithms with cross-functional partners.

Key Requirements

•Bachelor’s degree or above in math, statistics, computer science, industrial engineering, supply chain/logistics, operations research, or related fields.
•Strong data structures and algorithm design foundation; proficiency in at least one programming language such as Python, Java, C++, or R.
•Expertise in deep learning and reinforcement learning (including sequence decision-making and multi-agent RL), operations research optimization (integer and stochastic programming), and large models (LLM fine-tuning, multimodal large models).
•Prefer logistics/supply-chain experience with relevant algorithm implementation.
•Strong learning ability, clear logic, teamwork and communication skills, and proficient English writing/communication.

Experience:LogisticsSupply chain

Education:Bachelor's

Skills:Learning abilityCuriosityClear logicTeamworkCommunication

Languages:English

Company Brief

ByteDance

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn