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About This Role
AI Marketing & Web Operations Specialist
Brevard SEM is looking for someone who is comfortable working at the intersection of AI, digital marketing, and web development.
This role is for someone who already uses AI as part of their normal workflow — not just for writing content, but for building websites, solving problems, improving processes, researching, automating repetitive work, and helping projects move faster.
You do not need to be a senior developer or an expert in every area of digital marketing. What matters most is that you understand how websites and marketing systems work, you are resourceful, and you know how to use AI tools to get from an idea to a finished result.
What You’ll Be Doing
You’ll work alongside our marketing and development team on a variety of client and internal projects, including:
- Building and updating websites and landing pages
- Working in WordPress and Shopify
- Using AI to assist with development, troubleshooting, research, and production
- Helping with SEO, content implementation, and technical website work
- Creating simple automations and improving internal workflows
- Working with APIs, forms, CRMs, email, SMS, and third-party tools
- Reviewing AI-generated content and code before it goes live
- Troubleshooting website and integration issues
- Testing new AI tools and finding practical ways to use them within the agency
- Helping turn ideas and strategies into finished deliverables
- Documenting repeatable processes that can be used across multiple accounts
What We’re Looking For
We’re looking for someone who is naturally curious, technically capable, and good at figuring things out.
You should have experience with some combination of:
- ChatGPT, Claude, Gemini, Cursor, Copilot, or similar tools
- WordPress and/or Shopify
- HTML and CSS
- Basic JavaScript or general development knowledge
- GitHub
- APIs and integrations
- SEO and digital marketing
- Automation tools such as Zapier, Make, or n8n
- Google Analytics and Search Console
You do not need to check every box.
We are more interested in someone who can learn quickly and work through problems than someone who simply has a long list of software on their resume.
The Right Person for This Role
You’re probably a good fit if you regularly use AI to make your work faster or better.
Maybe you have used it to build a website, fix code, create an automation, analyze data, connect two systems, research a problem, or improve a marketing campaign.
You should be comfortable being given a goal without always being given step-by-step instructions.
We want someone who can look at a problem, figure out the best way to approach it, and keep working until it is solved.
Just as important, you should know that AI is not always right. You need to be able to review the work, catch mistakes, and make sure the final product is something we would feel comfortable putting in front of a client.
Bonus Experience
Experience in any of the following is a plus:
- OpenAI API
- AI agents or voice agents
- Node.js or TypeScript
- Next.js
- Python
- CRM integrations
- Twilio or Telnyx
- Google Ads
- Technical SEO
- Local SEO
- AEO / GEO
- AI image or video tools
- SaaS development
About Brevard SEM
Brevard SEM is a digital marketing agency working with businesses across SEO, paid advertising, web development, content, local search, reputation management, and emerging AI technology.
Our team is actively incorporating AI into how we build, research, analyze, and execute client work, and this position will help us continue expanding that capability.
How to Apply
Please send your resume and portfolio to:
Along with your resume, we would like to see a few examples of things you have actually worked on.
Websites, automations, applications, campaigns, or other projects are all welcome.
If AI played a role in the project, tell us briefly how you used it and what you were able to accomplish.
You can also call the Brevard SEM office directly if you would like to introduce yourself and discuss the position.
Pay: $15.00 - $30.00 per hour
Benefits:
- Paid time off
- Professional development assistance
Work Location: In person
Salary Context
This $31K-$62K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $176K across 1540 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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Brevard SEM, 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 $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($46K) sits 78% below the category median. Disclosed range: $31K to $62K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Brevard SEM AI Hiring
Brevard SEM has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Melbourne, FL, US. Compensation range: $62K - $62K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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