Head of Applied Machine Learning

Gametime

Applied ML leader developing ranking, personalization, and LLM systems for Gametime’s live-event ticketing platform. Leading practitioners and delivering production models that improve customer experience and business outcomes.

Posted 8/7/2026full-timeRemote • 🇺🇸 United StatesLead💰 $292,033 - $343,568 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production machine learning models, with a focus on ranking, recommendation, and personalization systems. Proficient in applying LLMs and hybrid ML techniques to enhance semantic understanding and content generation while establishing best practices for model deployment and monitoring.

Highest-signal resume keywords

Machine Learning Model DevelopmentRanking And Personalization SystemsLLM Experience And Prompt EngineeringSoftware Engineering SkillsCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModeling ApproachesFeature StrategyEvaluation MetricsLearning-To-RankEmbeddingsGradient BoostingNeural NetworksFine-TuningRetrieval-Augmented Generation

Soft Skills

MentoringInfluencing Without Hierarchy

Tools & Technologies

Data StacksML Stacks

Industry Keywords

Production ReadinessExperimentation DisciplineModeling RigorBest PracticesScalable Deployment

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

Equal opportunity employer committed to an inclusive environment
Diversity and belonging initiatives
Compensation range of $292,033–$343,568 USD per year