Interested in this AI/ML Engineer role at Master Your Message?
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About This Role
Overview
This is a fully remote position, writing strategy\-led website copy exclusively for mental health practitioners (therapists, counsellors, psychologists, psychotherapists, and group practice owners) across Canada and the US. You'll work from client intake documents to develop a clear first\-step message strategy, then write, edit, and proofread original website copy that moves a reader to act. AI has become core to how we work, but the thinking, judgment, and final words are yours.
This space comes with real constraints. Copy has to respect what colleges and regulatory boards allow practitioners to say (don’t worry, we will teach you!). Part of the craft here is writing copy that converts while staying within those lines.
What you'll do
- Understand each client's business goals and who they're trying to reach
- Develop a strategy that gets results
- Use AI to synthesize and extract detail from client documents, paired with your own manual review
- Write compelling, original copy aligned to the client's goals, strategy, and audience
- Write bio pages that tell a real story and leave people feeling like this is the person they want to work with
- Write specialty pages (following our templates) with keywords worked in naturally
- Match each client's tone, style, and voice
- Edit with precision, including knowing when a client suggestion shouldn't be implemented
- Attend client\-facing meetings when a project calls for it (occasional, and not every project)
- Proofread final documents and prepare them for development
- Follow our SOPs and templates
How we use AI
AI is a non\-negotiable tool here. We use it to synthesize information, analyze, and draft. But raw AI output is rarely good enough. It's often generic, leans on clichés, and says nothing that moves the story forward. Your job is to question what comes out of these models, cut what's empty, and shape it into copy that actually works. If you think AI output is the gold standard, this isn't the role for you. If you treat it as a fast first draft you're responsible for fixing, you'll thrive.
Requirements
- Follow the StoryBrand process
- Use AI fluently as part of your daily workflow
- SEO knowledge, plus AEO/LLM/AI\-search knowledge (or a real willingness to learn it)
- Familiarity with: Claude and ChatGPT (or comparable AI tools), Loom, Google Drive, Canva, SEMrush (or a comparable SEO tool), Grammarly (or comparable proofreading tools)
- Represent the tone, style, and voice of each client in your copy
- High attention to detail: consistent capitalization, punctuation, Oxford commas, grammar, and US vs Canadian spelling
- Understand website structure well enough to indicate SEO tags and place call\-to\-action buttons
- Thrive in a fast\-paced environment where deadlines are firm and matter
- Work independently and as part of a team
- Willingness to work within our established systems and templates
- Strong organizational skills and the ability to juggle multiple projects at once
- Reliable high\-speed internet
Experience \& qualifications
This can suit a junior copywriter, but you must bring:
- An understanding of storytelling and how to use it to sell
- An understanding of marketing and how people actually make buying decisions
- Compassion, and a real interest in the mental health space
- Fluent English with demonstrated writing, editing, and proofreading ability
- The ability to work efficiently and prioritize across multiple projects
Pay
$28\-32
Schedule
- Make your own schedule outside of client meetings
- Available 9–5 EST, Monday to Friday, for client meetings
- Projected 20–30 hours per week (with additional time if needed)
Location
Open to candidates in Canada.
How To Apply:
Complete the Google Form below to submit your resume. You will be asked to share 2 writing samples. In the field asking, “What is your Enneagram Type?” write the word “Websites” before entering your number:
https://forms.gle/1DjoC6FU3e68HfjPA
Job Type: Freelance
Pay: $24\.00 \- $32\.00 per hour
Benefits:
- Flexible schedule
Experience:
- copywriting: 2 years (Preferred)
Work Location: Remote
Salary Context
This $49K-$66K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Master Your Message, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($58K) sits 68% below the category median. Disclosed range: $49K to $66K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Master Your Message AI Hiring
Master Your Message has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $66K - $66K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.
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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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