---
title: 'Head of Applied Machine Learning at Gametime United'
canonical: 'https://feeny.ai/job/head-of-applied-machine-learning-gametime-united-united-states-rdxsdmcj3j2h'
type: 'job'
last_seen: '2026-09-14'
---

# Head of Applied Machine Learning at Gametime United

- **Company:** Gametime United
- **Location:** United States
- **Compensation:** $292k–$344k
- **Work type:** remote
- **Posted:** 2026-01-15
- **Last confirmed live:** 2026-09-14
- **Apply:** https://job-boards.greenhouse.io/gametimeunited/jobs/5071620008

## Job description

About Us:

Live experiences help people cross today’s digital divide and focus on what truly connects us – the here, the now, this once-in-a-lifetime moment that’s bringing us together. To fulfill Gametime’s mission of uniting the world through shared experiences, we make it easy for people to discover and access the live experiences that matter most.

With platforms on iOS, Android, mobile web and desktop supporting more than 60,000 events across the US and Canada, we are reimagining the event ticket industry in order to move at the speed of life.

Position Summary

Gametime is seeking a Head of Applied Machine Learning to lead the development and application of machine learning and LLM-powered models that drive meaningful business impact across product, marketing, operations, and other key functions. This role is ideal for a hands-on, applied ML leader who thrives at the intersection of modeling excellence and business understanding. You will work closely with Product, Data, Engineering, and business partners to identify high-value opportunities, translate them into well-defined modeling problems, and deliver production-ready solutions. A core focus of this role will be curation, including ranking, filtering, and personalization systems that directly shape the customer experience, alongside thoughtful application of modern LLM-based techniques.

## Who You Are

- An experienced applied ML practitioner with a track record of delivering production models that move business metrics
- Deeply comfortable owning ranking, recommendation, and curation problems from framing through iteration in production
- Experienced applying both classical ML techniques and LLM-based approaches with strong technical judgment
- A player-coach who can review code, guide modeling decisions, and mentor ML practitioners
- Business-oriented, seeking context, tradeoffs, and outcomes rather than purely technical elegance
- Comfortable managing multiple initiatives across stakeholders and timelines
- A clear communicator who can translate complex ML concepts into business-relevant insights
- Curious and motivated to stay current with applied ML and LLM advancements

## What You Will Work On

Applied ML and Business Alignment

- Partner with Product, Marketing, Operations, and other teams to identify where ML can drive measurable value
- Translate business problems into clear modeling objectives, metrics, and experimentation plans
- Ensure ML efforts remain tightly aligned with business priorities and user impact

Ranking, Curation, and Personalization

- Lead the design, development, and iteration of ranking, filtering, and personalization models across Gametime’s product surfaces
- Own modeling approaches, feature strategy, evaluation metrics, and offline and online experimentation
- Balance relevance, revenue, and user trust when evolving ranking solutions

LLM and Advanced Modeling Applications

- Apply LLMs and hybrid ML techniques to use cases such as semantic understanding, intent detection, content generation, and internal workflows
- Evaluate emerging tools and techniques, recommending pragmatic adoption where they provide clear benefit
- Establish best practices for testing, deploying, and monitoring LLM-powered models in production

## Team Leadership and Craft Excellence

- Manage and mentor applied ML practitioners, supporting growth in technical depth and business impact
- Set high standards for modeling rigor, experimentation discipline, and production readiness
- Collaborate closely with ML engineering and platform teams to ensure scalable and reliable deployment

## Experience You Bring

- Bachelor’s degree in Computer Science, Engineering, or a related field (advanced degree preferred)
- 6+ years of experience building and deploying production machine learning models
- Demonstrated experience owning ranking, recommendation, or personalization systems
- Strong foundation in applied ML techniques such as learning-to-rank, embeddings, gradient boosting, and neural networks
- Hands-on experience working with LLMs, including prompt engineering, fine-tuning, retrieval-augmented generation, and evaluation
- Solid software engineering skills and experience working within modern data and ML stacks
- Proven ability to work cross-functionally and influence without relying on hierarchy

What Success Looks Like

- Applied ML solutions that measurably improve customer experience and business outcomes
- High-quality, continuously improving ranking and curation systems
- Thoughtful, value-driven use of LLMs rather than novelty applications
- Strong partnership with product and business teams, with ML viewed as a strategic enabler
- A supported, high-performing applied ML team delivering consistent impact

At Gametime pay ranges are subject to change and assigned to a job based on specific market median of similar jobs according to 3rd party salary benchmark surveys. Individual pay within that range can vary for several reasons including skills/capabilities, experience, and available budget.

United States - Pay Range $292,033—$343,568 USD

Gametime is committed to bringing together individuals from different backgrounds and perspectives. We strive to create an inclusive environment where everyone can thrive, feel a sense of belonging, and do great work together. As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, veteran status, sex, parental status, gender identity or expression, transgender status, sexual orientation, national origin, age, disability or genetic information. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our company.

## About Gametime United

## Company Overview
- **One-liner**: Gametime provides a mobile-first marketplace for last-minute tickets to sports, music, and theater events, enabling users to purchase and access tickets directly from their phone.
- **Entity Type**: Private (Privately Held)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2013
- **Founders**: Brad Griffith

## Core Business
- **Primary industry/industries**: Entertainment, Live Events, Ticketing Technology
- **Target customers**: B2C (individual fans seeking last-minute event tickets)
- **Mission or purpose statement**: "Uniting people through shared experiences" by building technology that gets people out into the real world together.

## Products & Services
- **Gametime Marketplace**: A mobile-first platform (iOS and Android) offering last-minute tickets to sports, music, comedy, and theater events in over 60 cities across the U.S. and Canada. Key features include:
    - **All-In Pricing**: Transparent upfront pricing with no hidden fees.
    - **Gametime Guarantee**: Assurance that tickets will be valid and delivered in time for the event.
    - **Real-Time Pricing Engine**: Dynamic pricing powered by machine learning.
    - **AI-Driven Personalization**: Sub-second checkout and tailored recommendations.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed as a private company.
- **Key Metric**: Total Funding: **$71.6M**
- **Annual Revenue**: Approximately **$24.0M** (per LinkedIn data)
- **Notable Investors/Partners**: Accel, Evolution Media, Nimble Partners, Techstars
- **Growth Signals**: Operates in 61 cities across the US & Canada; over 148,000 teams and artists on the platform; 5,423 events listed. The company is actively hiring across Engineering, Product, Data, and Growth, with a stated "AI-First" strategy.

## Competitive Advantages
- **Mobile-First, Last-Minute Focus**: Built from the ground up for on-the-go, spontaneous ticket purchases, differentiating from legacy players who rely on desktop/printer-centric models.
- **AI-First Toolkit**: Every team is empowered to use AI to automate, experiment, and ship faster, creating a tech-forward edge.
- **Founder Mentality Culture**: Hires people who thrive with autonomy, ownership, and a long leash, aiming to attract high-impact talent that moves the needle.
- **Proprietary Technology**: Real-time pricing engine, ML-driven recommendations, and a sub-second mobile checkout are core competitive moats.

## Strategic Focus
- **Remote-First Expansion**: Hiring across 25+ US states with a fully remote setup, no hybrid or mandatory office days.
- **Product & Engineering Investment**: Actively hiring for Staff Engineer, Fullstack Engineer, and Front End Engineer roles to build out the technology stack.
- **Data-Driven Growth**: Scaling CRM, paid search, and SEM efforts to drive fan acquisition.
- **AI Integration**: Continuing to integrate AI across the product and internal operations as a core strategic lever.

## Why Work Here
- **Remote-First Culture**: Fully remote company spanning 25+ US states with no mandatory office days. The company invests in bringing people together for team events throughout the year.
- **Competitive Compensation & Equity**: Offers a "competitive comp" package including an ownership stake in the company.
- **Generous Benefits**: Medical, dental, and vision coverage; paid parental leave; mental wellness support (Lyra Health); open PTO (with a claim that they actually mean it); home office allowance; and "Gametime Credit" to attend events monthly.
- **Engineering Culture**: Described as "fast and build to last" with a bias for shipping. The technology stack includes real-time pricing engines, ML models, and AI-driven personalization. A focus on founder mentality means small teams and big ownership.
- **Hiring Process**: Designed to be fast and transparent, with a 30-minute recruiter chat (may include an AI interviewer), a skills assessment for some roles, and team interviews. The company states they review every application.
- **Recent Leadership**: Brad Griffith (CEO & Founder), Mihir Sambhus (CTO), Danny Guillory (CPO), Dave Zaragoza (CFO), Jon Armitage (CGO).

## Sources
1. [gametime.co - Careers Page](https://gametime.co/company/careers/)
2. [gametime.co - About Us](https://gametime.co/company/about/)
3. [LinkedIn - Gametime United](https://www.linkedin.com/company/gametime-united)
4. [Built In - Gametime United](https://builtin.com/company/gametime-united/faq/workplace-perception)

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