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: 2 minutes agoStatus: Live

Job Summary

Build and implement AI and operations research algorithms for TikTok’s logistics fulfillment systems across first-, middle-, and last-mile scenarios. You’ll apply deep reinforcement learning and large-model techniques to improve routing, order batching, wave picking, packaging, scheduling, and network planning. Collaborate with cross-functional teams to productize algorithms, simulate complex supply chain scenarios, and develop multimodal innovations for warehouse identification and traceability.

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 warehouses, including deep reinforcement learning for intelligent order batching, wave picking, and dynamic packaging optimization.
•Lead algorithm construction for first-mile/last-mile scenarios: route planning, merchant onboard/offboard decisions, regional division, and delivery-station-level order allocation and GTL code prediction.
•Build LLM-driven intelligent labor scheduling optimization using business rules and real-time capacity fluctuations to improve last-mile fulfillment efficiency.
•Develop logistics backbone network planning capabilities using large language model-based simulation to assess timeliness, traffic, and profit impacts, optimizing network layout decision-making efficiency.
•Research and develop intelligent scheduling algorithms for middle-mile scenarios and explore multimodal AI innovations for warehouse identification, missing-part detection, and automatic abnormal traceability.

Key Requirements

•Bachelor’s degree or above in mathematics, statistics, computer science, industrial engineering, supply chain/logistics, operations research, or related fields.
•Solid data structures and algorithm design foundation, and proficiency in at least one programming language (Python, Java, C++, or R).
•Proficiency in deep learning and reinforcement learning (including sequence decision-making and multi-agent RL), plus operations research optimization (integer/stochastic programming).
•Experience with large models, including LLM application fine-tuning and multimodal large models, preferably in logistics or supply chain.
•Strong learning ability, curiosity, and clear logic, with good teamwork/communication and proficient English writing.

Experience:LogisticsSupply chain

Education:Bachelor's

Skills:Learning abilityCommunicationTeamworkCuriosityLogical thinking

Languages:English

Tech Stack:PythonJavaC++RDeep learningReinforcement learningMulti-agent reinforcement learningSequence decision-makingInteger programmingStochastic programmingLarge modelsLLM fine-tuningMultimodal large modelsLLM-driven schedulingImage recognition

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

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: 2 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 warehouses, including deep reinforcement learning for intelligent order batching, wave picking, and dynamic packaging optimization.
•Lead algorithm construction for first-mile/last-mile scenarios: route planning, merchant onboard/offboard decisions, regional division, and delivery-station-level order allocation and GTL code prediction.
•Build LLM-driven intelligent labor scheduling optimization using business rules and real-time capacity fluctuations to improve last-mile fulfillment efficiency.
•Develop logistics backbone network planning capabilities using large language model-based simulation to assess timeliness, traffic, and profit impacts, optimizing network layout decision-making efficiency.
•Research and develop intelligent scheduling algorithms for middle-mile scenarios and explore multimodal AI innovations for warehouse identification, missing-part detection, and automatic abnormal traceability.

Key Requirements

•Bachelor’s degree or above in mathematics, statistics, computer science, industrial engineering, supply chain/logistics, operations research, or related fields.
•Solid data structures and algorithm design foundation, and proficiency in at least one programming language (Python, Java, C++, or R).
•Proficiency in deep learning and reinforcement learning (including sequence decision-making and multi-agent RL), plus operations research optimization (integer/stochastic programming).
•Experience with large models, including LLM application fine-tuning and multimodal large models, preferably in logistics or supply chain.
•Strong learning ability, curiosity, and clear logic, with good teamwork/communication and proficient English writing.

Experience:LogisticsSupply chain

Education:Bachelor's

Skills:Learning abilityCommunicationTeamworkCuriosityLogical thinking

Languages:English

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn