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About This Role
What if the work you did helped someone change their life for the better?
Centerpointe Research Institute is looking for an AI Content Producer who already treats artificial intelligence as a core part of the creative process.
We are not looking for someone who has merely experimented with ChatGPT a few times. We are looking for someone who has favorite tools, strong prompting habits, and firsthand experience turning ideas, copy, and scripts into polished emails, videos, and audio.
You will work across several formats, but the purpose behind them will remain the same: helping people use Centerpointe’s programs to reduce stress, sleep better, meditate more deeply, and create meaningful change in their lives.
About Centerpointe
For more than 36 years, Centerpointe Research Institute has been a pioneer in neuroaudio technology. Our Holosync programs have helped more than 2\.2 million people around the world reduce stress, sleep better, meditate more deeply, and think more clearly.
We are a small, fast\-moving marketing team where each person’s work has a direct and visible impact. Email is our primary way of reaching our audience, but this role will also help us expand what we can create through AI\-assisted video, audio, and automation.
What You’ll Do
You will receive copy, scripts, creative direction, and source material from our marketing, copy, web, and design teams. Your job is to turn those materials into finished, polished content using AI tools, production software, and thoughtful human judgment.
Email Production
- Build, format, test, and schedule emails in Mailchimp and similar email platforms
- Ensure emails display correctly across devices and email clients
- Assist with A/B tests and review performance data
- Use AI\-assisted analysis and testing to help improve engagement and email performance
- Catch formatting, messaging, link, and quality issues before campaigns go live
AI Video and Audio Production
- Create videos using HeyGen and similar AI tools for lead magnets, social content, promotional campaigns, and course materials
- Produce narration, affirmations, meditation tracks, and other audio using ElevenLabs and comparable AI voice platforms
- Work with both AI\-generated audio and traditional recording, mixing, and editing software and tools.
- Edit and finish video and audio using Adobe Premiere Pro, After Effects, Canva, and professional recording equipment
- Turn rough concepts or scripts into polished, audience\-ready content
AI Workflow Development
- Use generative AI tools daily to accelerate and improve creative production
- Develop prompts, templates, and repeatable workflows for email, video, and audio projects
- Explore new AI tools and identify practical ways the marketing team can use them
- Recommend processes that can be automated, streamlined, or improved
- Help the team understand what is currently possible with AI, including where human review is still essential
Quality Control
- Catch factual errors, visual inconsistencies, unnatural language, pronunciation issues, and other problems created by AI
- Keep content aligned with Centerpointe’s brand, message, and quality standards
- Make sure everything we publish is not only fast to produce, but also genuinely good
- Review your own work carefully before it reaches the final approval stage
What You’ll BringRequired
- Frequent, hands\-on use of generative AI tools such as ChatGPT, Claude, or similar platforms for real content production
- Experience prompting, revising, and refining AI output rather than accepting the first result
- Experience with at least one AI video platform, such as HeyGen or Synthesia
- Experience with at least one AI voice platform, such as ElevenLabs
- Experience building emails in Mailchimp or a comparable email service provider
- Working proficiency in Adobe Premiere Pro and Canva
- Familiarity with After Effects or a willingness to develop stronger skills in it
- A basic understanding of A/B testing and email performance metrics
- Strong attention to detail and the ability to recognize when AI\-generated content is inaccurate, awkward, or off\-brand
- The ability to manage several types of production work while meeting deadlines
Helpful, but Not Required
- Experience creating AI agents or multi\-step automated workflows
- Basic API knowledge or light coding experience
- Experience operating professional recording equipment
- Familiarity with image\-generation tools, editing assistants, and other AI creator platforms
- Experience producing meditation, educational, wellness, or personal\-development content
What Sets the Right Person Apart
You do not need years of experience in this exact position. The role barely existed in its current form a few years ago.
What matters is that you are already wired to use AI as part of how you create. You enjoy experimenting, troubleshooting, and finding the workflow no one has automated yet. You are curious about new technology, but you are not impressed by novelty alone. You care about whether the finished work is accurate, useful, polished, and worth someone’s attention.
You understand that AI can make production faster, but human taste and judgment are what make the result good.
What We Offer
- Salary of $47,000 to $55,000, based on experience
- Health, dental, and vision insurance
- Paid time off
- A stable company with more than 36 years in business
- A small, collaborative team where your contributions are visible
- The opportunity to help shape how an established company uses emerging AI technology
- Work connected to a mission that meaningfully affects people’s lives
Why Work Here?
Many marketing jobs ask you to sell things. This role asks you to use the newest creative tools available to help people make meaningful changes in their lives.
Our customers are not simply buyers. They are people who tell us they have slept through the night for the first time in months, finally developed a meditation practice, or found the clarity to face something they had avoided for years.
That is what sits behind every email, video, and audio track you will help create.
Pay: $47,000\.00 \- $55,000\.00 per year
Benefits:
- Health insurance
- Paid time off
- Vision insurance
Work Location: In person
Salary Context
This $47K-$55K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Centerpointe Research Institute, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($51K) sits 76% below the category median. Disclosed range: $47K to $55K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Centerpointe Research Institute AI Hiring
Centerpointe Research Institute has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Hillsboro, OR, US. Compensation range: $47K - $55K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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