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About This Role
Popmenu is building the future of restaurant marketing, and partnerships are a major growth engine.
We're looking for a creative, AI\-savvy Marketing \& Content Creator to help bring partnership ideas to life through compelling content, design, and storytelling. You'll work directly with the Head of Partnerships and Partnerships Manager to transform concepts into polished marketing assets, videos, campaigns, and sales materials that partners are excited to share and customers actually engage with.
This role is ideal for someone who blends creativity with emerging AI tools and enjoys turning ideas into impactful content quickly. You'll have meaningful ownership, direct exposure to leadership, and the opportunity to help shape how Popmenu shows up across the restaurant technology ecosystem.
Requirements What You'll Do
You will be responsible for the creative execution of partnership marketing initiatives, including:
- Designing marketing collateral, including one\-pagers, pitch decks, partner playbooks, and co\-branded assets
- Creating email campaign visuals and supporting content for partner and customer communications
- Developing sales enablement materials that help drive partnership revenue
- Producing social media content, including LinkedIn, Instagram, and short\-form video content
- Creating and editing video assets for product launches, partner campaigns, customer stories, webinars, and social channels
- Using AI\-powered creative tools such as Claude, Claude CoWork, Claude Design, ChatGPT, Canva AI, and similar platforms to accelerate content creation and creative workflows
- Writing, refining, and optimizing prompts to generate marketing copy, campaign concepts, visual assets, and presentation materials
- Translating loose ideas, outlines, and brainstorming sessions into polished, high\-quality deliverables
- Experimenting with emerging AI, video, and content formats to help define what great partnership marketing looks like
- Managing multiple projects simultaneously while owning timelines, revisions, and execution
- Measuring content performance and continuously improving creative output based on engagement and feedback
You won't just execute requests. You'll help shape how Popmenu and our partners tell their stories.
What We're Looking For
- Strong visual design skills across digital, social, and presentation formats
- Experience with Figma, Adobe Creative Suite, Canva, or similar design platforms
- Experience creating and editing video content for social media, marketing campaigns, or brand storytelling
- Familiarity with AI\-powered content creation tools, including Claude, Claude CoWork, Claude Design, ChatGPT, Midjourney, Runway, Canva AI, or similar platforms
- Ability to write effective prompts and leverage LLMs to improve creative workflows
- Strong writing, storytelling, and content development skills
- Ability to take feedback and iterate quickly
- Exceptional attention to detail and a strong sense of ownership
- Curiosity about emerging technology, AI, and modern marketing practices
- Passion for creativity, storytelling, and building something from scratch
Bonus Points
- Experience creating content for SaaS, technology, restaurants, hospitality, or local businesses
- Photography, videography, or motion graphics experience
- Experience managing social media channels or content calendars
- Experience building presentations for executives, partners, or sales organizations
Why This Role Is Fun
- Your work will be used immediately by real partners, customers, and sales teams
- You'll have creative freedom with visible business impact
- You'll help shape how Popmenu partners show up in the restaurant industry
- You'll work directly with leadership and have a seat at the table
- You'll get hands\-on experience with cutting\-edge AI tools and content creation workflows
- Restaurants are one of the most creative, human industries there is — and we serve them
Benefits What We're Serving
- Genuine Core Values with quarterly peer recognition through our Super Booms
- Giving Back with company donations to causes chosen by team members
- Visible Growth and Development in a scaling SaaS company
- Company Ownership with meaningful equity for every employee
- Comprehensive Benefits including medical, dental, vision, 401(k), and Wagmo Wellness Plan for your pets
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Popmenu, LLC, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $178,940 based on 11,900 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Popmenu, LLC AI Hiring
Popmenu, LLC has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in US.
Location Context
AI roles in Austin pay a median of $218,800 across 493 tracked positions. That's 9% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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