
201 - 500 employees
🛍️ eCommerce
⚽ Sports
eCommerce • Entertainment • Sports
Gametime is a platform that offers last-minute ticket deals for sports, music, theater, and other live events. Users can access tickets for a wide range of events, including college football, concerts, comedy shows, theater performances, and professional sports leagues such as the NFL, NBA, MLB, NHL, and MLS. The platform emphasizes a user-friendly experience with features like all-in pricing to avoid hidden fees and a lowest price guarantee. Gametime aims to provide an easy and affordable way for users to experience live entertainment in various cities across North America.
🕒 August 7
🇺🇸 United States – Remote
💵 $292k - $343.6k / year
⏰ Full Time
🔴 Lead
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
👻 Ghost score 3%
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201 - 500 employees
🛍️ eCommerce
⚽ Sports
eCommerce • Entertainment • Sports
Gametime is a platform that offers last-minute ticket deals for sports, music, theater, and other live events. Users can access tickets for a wide range of events, including college football, concerts, comedy shows, theater performances, and professional sports leagues such as the NFL, NBA, MLB, NHL, and MLS. The platform emphasizes a user-friendly experience with features like all-in pricing to avoid hidden fees and a lowest price guarantee. Gametime aims to provide an easy and affordable way for users to experience live entertainment in various cities across North America.
• Partner with Product, Marketing, Operations, and other teams to identify where ML can drive measurable value • Translate business problems into modeling objectives, metrics, and experimentation plans • Lead design, development, and iteration of ranking, filtering, and personalization models • Own modeling approaches, feature strategy, evaluation metrics, and offline and online experimentation • Apply LLMs and hybrid ML techniques to semantic understanding, intent detection, content generation, and internal workflows • Evaluate emerging tools and recommend pragmatic adoption • Establish best practices for testing, deploying, and monitoring LLM-powered models in production • Manage and mentor applied ML practitioners • Set standards for modeling rigor, experimentation discipline, and production readiness • Collaborate with ML engineering and platform teams on scalable, reliable deployment
• Bachelor’s degree in Computer Science, Engineering, or a related field • 6+ years of experience building and deploying production machine learning models • Experience owning ranking, recommendation, or personalization systems • Knowledge of learning-to-rank, embeddings, gradient boosting, and neural networks • Hands-on LLM experience, including prompt engineering, fine-tuning, retrieval-augmented generation, and evaluation • Solid software engineering skills and experience with modern data and ML stacks • Ability to work cross-functionally and influence without hierarchy • Advanced degree preferred
• Equal opportunity employer committed to an inclusive environment • Diversity and belonging initiatives • Compensation range of $292,033–$343,568 USD per year
Apply Now🕒 August 6
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