AHU Technologies Inc

Machine Learning Engineer - Recommendation Systems - Mandarin Required

AHU Technologies Inc · United States · $150K–$3M/yr

Staffing and Recruiting · 51-200 employees

5 h ago
Remote Senior (5-10 yrs) Full-time United States
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About the role

Own the recommendation, search, ranking, and discovery systems for Sekai's content ecosystem. Design, launch, and analyze experiments to improve retrieval and serving quality.

What they look for

Machine Learning Recommendation Systems Search Ranking Retrieval Systems Two-Tower Models Embedding Retrieval Candidate Generation Online Evaluation Offline Evaluation Experiment Design Mandarin Proficiency

Requirements

Requires 5+ years of industry experience building production ML systems with a focus on recommendation or search. Must have hands-on experience with two-tower models, embeddings, and engagement-driven consumer products.

Full description

JD in one line

Own recommendation, search, ranking, retrieval, and discovery for Sekai’s content ecosystem.

What you will own

· Build recommendation and search across feed, discovery, search, and content continuation.

· Own retrieval/ranking: candidate generation, embeddings, two-tower models, features, and serving quality.

· Design, launch, and analyze recommendation/search experiments.

Requirements

· years industry experience building production ML systems with senior ownership.

· 5+ Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.

· Consumer apps, entertainment, social, gaming, creator, or engagement-driven products.

· Two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.

Hard filters

· 5+ years industry experience building production ML systems with senior ownership.

· Hands-on recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.

· Consumer apps, entertainment, social, gaming, creator, or engagement-driven products.

· Two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.

Strong fit

· Build recommendation and search across feed, discovery, search, and content continuation.

· Own retrieval/ranking: candidate generation, embeddings, two-tower models, features, and serving quality.

· Design, launch, and analyze recommendation/search experiments.

Bonus:

Bonus signal: 5+ years production ML

Bonus signal: recommendation systems

Bonus signal: search ranking

Bonus signal: embedding retrieval

Anti-signals

· Cannot show core Senior Machine Learning Engineer, Recommendation experience

· Not comfortable with the listed work mode

Low ownership, coordination-only, or no shipped examples

This is a remote position.