Algorithm Engineer Intern, Global Live Revenue ML

Collaw; Sydney; Hybrid; AUD 34,000 - 55,000; Part time

Job summary

TikTok LIVE Revenue internship offers PhD or Master students a hands‑on opportunity to contribute to cutting‑edge ML systems powering global LIVE activities. You will apply your research and ML expertise to optimize algorithms that drive engagement and business growth, while collaborating with product and operations teams.

You will design, train, and deploy scalable models for recommendations, ranking, targeting, and performance optimization, shaping long‑term algorithm strategies and roadmap.

Qualifications

• Pursuing PhD or Master in math, physics, statistics, AI, software engineering, CS or related field.
• Knowledge in ML/DL/LLM/agent/causal inference.
• Familiar with data-centric domains: recommendation, generation, A/B testing.
• Excellent communication and ownership.

Responsibilities

• Build and optimize ML systems for global LIVE activities.
• Analyze activity data, develop strategy models, and use data-driven approaches to improve engagement and growth.
• Design, train, and deploy scalable models for recommendation, ranking, targeting, and performance optimization.
• Understand business objectives and collaborate with product/operations on long‑term algorithm roadmap.
• Collaborate with cross‑functional teams to improve model performance and business impact.

Skills

Machine learning

Deep learning

LLM

Causal inference

Education

PhD or Master in math, physics, statistics, AI, CS

Job description

TikTok LIVE Revenue internship offers PhD or Master students a hands‑on opportunity to contribute to cutting‑edge ML systems powering global LIVE activities. You will apply your research and ML expertise to optimize algorithms that drive engagement and business growth, while collaborating with product and operations teams.

You will design, train, and deploy scalable models for recommendations, ranking, targeting, and performance optimization, shaping long‑term algorithm strategies and roadmap.