Interested in this AI/ML Engineer role at World Emblem International?
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About This Role
We are the world’s largest emblem manufacturer and embroidery services with 8 strategic locations throughout the US, Canada, Mexico, and Europe. We have been trusted year after year by customers for over 30 years to provide high\-quality products and embroidery services that help customers create a great look, have memorable experiences, and promote their brand. We offer a wide variety of emblem options, ranging from traditional embroidered to FlexStyle patches and everything in between. Our culture is represented by our Core Values: Stay positive, Get the Job Done, Customer Centricity and 100% Committed to the team.
JOB SUMMARY
You'll manage paid media strategy and execution across Meta, Google, TikTok, and other platforms for three ecommerce brands. This is hands\-on work — you'll be in the accounts daily, optimizing campaigns, testing creative, and driving measurable revenue growth. You'll report to the Director of Ecommerce and Digital Marketing.
ESSENTIAL DUTIES AND RESPONSIBILITIES
- Identify new channels and growth opportunities
- Plan, build, and optimize campaigns across Meta Ads, Google Ads (Search, Shopping, Performance Max), TikTok Ads, and LinkedIn Ads
- Manage six\-figure monthly ad spend across multiple brands and platforms
- Own performance metrics: ROAS, CAC, contribution margin, incrementality
- Develop and test audience strategies, creative concepts, and landing page variations
- Build and maintain reporting dashboards; deliver actionable insights to leadership
- Collaborate with creative team on ad assets, messaging, and promotional campaigns
- Stay current on platform changes, betas, and best practices
- Identify new channels and growth opportunities
QUALIFICATIONS
- 3\-5 years managing paid media for ecommerce or DTC brands
- Proven track record scaling campaigns profitably on Meta and Google
- Experience with TikTok Ads a plus; eager to learn new platforms
- Strong analytical skills — comfortable in GA4, Excel/Sheets, and BI tools
- Understanding of attribution challenges and how to navigate them
- Creative eye — you know what makes an ad stop the scroll
- Self\-starter mentality; you don't wait to be told to optimize
- Clear communicator who can translate data into decisions
SKILLS
Full\-funnel campaign planning
- ROAS \& CAC optimization
- Incrementality testing
- Creative strategy \& testing frameworks
- Landing page optimization
- Competitive analysis
- New channel evaluation \& expansion
WORK ENVIRONMENT
- Fast\-paced, results\-driven — We're building a digital marketing operation from the ground up. You'll move quickly, test often, and own outcomes.
- Autonomy with accountability — No micromanagement. You'll have the freedom to run campaigns your way, with clear expectations on performance.
- Collaborative team — Work directly with leadership, creative, and ecommerce teams. Ideas get heard; good ones get implemented.
- Multi\-brand exposure — Manage campaigns across three distinct brands with different audiences, products, and strategies. No two days are the same.
- Real budget, real impact — Six\-figure monthly spend means your decisions matter. Wins are visible, and growth is measurable.
- Remote\-friendly flexibility — Remote or hybrid from our Miami headquarters. We care about output, not office hours.
- Learning culture — Platforms change constantly. We invest in staying current and encourage experimentation.
PHYSCIAL DEMANDS
- Prolonged periods sitting at a desk and working on a computer
- Must be able to operate standard office equipment (computer, keyboard, mouse, phone)
- Ability to view and read information on a computer screen for extended periods.
World Emblem is an Equal Opportunity Employer (EOE). Qualified applicants are considered for employment without regard to age, race, color, religion, sex, national origin, sexual orientation, disability, or veteran status.
World Emblem is proud to be a drug free workplace. All applicants will undergo a criminal background check, pre\-placement drug screen, and are in compliance with E\-Verify
Salary Context
This $75K-$80K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At World Emblem International, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($77K) sits 54% below the category median. Disclosed range: $75K to $80K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
World Emblem International AI Hiring
World Emblem International has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Hollywood, FL, US. Compensation range: $80K - $80K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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