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Part-Time AI Video & Content Marketing Intern
AMD Lasers | West Jordan, Utah Part-Time Paid Role | 15–25 Hours per Week | Flexible Around Class Schedule
About AMD Lasers
AMD Lasers is an innovative dental technology company located in West Jordan, Utah. We develop, manufacture, and market products used by dental professionals throughout the United States and around the world.
We are looking for a creative student to join our Marketing team in a part-time role focused on content creation, social media, and especially AI-powered video creation.
This is not an internship where you'll spend most of your time watching other people work. We want someone who is excited to experiment, create, and help us discover new ways to use AI to produce engaging marketing content.
What You'll Do
You'll work directly with AMD's Marketing team to create content that educates, entertains, and engages dental professionals. A major focus of the position will be exploring how generative AI can help us create more-and better-video content faster.
Projects may include:
- Creating short-form videos for Instagram, TikTok, YouTube, Facebook, LinkedIn, and other platforms
- Turning product concepts and marketing ideas into AI-generated video scenes
- Developing AI avatars, presenters, animations, and visual demonstrations
- Writing and refining prompts for AI video and image-generation platforms
- Combining AI-generated video with traditional product footage
- Creating product demonstrations and educational videos
- Developing motion graphics, captions, voiceovers, music, and other creative elements
- Creating social media graphics, images, and supporting marketing content
- Experimenting with new AI video, image, voice, and content-creation platforms
- Developing multiple creative versions of content for A/B testing
- Building a library of reusable digital content for AMD's products and brands
- We don't expect you to already know every platform. In fact, part of the job will be discovering new tools, testing them, and figuring out how AMD can use them.
What Could You Create?
- One week you might create a 15-second social video introducing a new dental product.
- The next week you might turn a traditional product photograph into an AI-generated video.
- You could create an animated explanation of how a dental laser works, transform a 45-minute educational webinar into ten pieces of short-form content, create an AI spokesperson for a campaign, develop a humorous social video, or test five completely different creative approaches to see which generates the most engagement.
- Some projects will be polished and professional.
- Others may be weird, funny, experimental, or completely unexpected.
- We want someone willing to try things.
Who We're Looking For
This role could be a great fit for a student studying: Marketing • Digital Marketing • Communications • Film & Video Production • Digital Media • Graphic Design • Animation • Advertising • Content Creation • AI / Emerging Media
You don't need extensive professional experience.
We're more interested in your creativity, curiosity, technical aptitude, and ability to turn an idea into something people actually want to watch.
An ideal candidate:
- Loves creating videos and digital content
- Is fascinated by generative AI
- Regularly experiments with new technology
- Understands what makes short-form social content interesting
- Has a good visual eye
- Can tell a story quickly
- Enjoys experimenting with different creative concepts
- Isn't afraid to create something, discover that it doesn't work, and try again
- Can work independently and take an idea from concept through finished content
- Pays attention to trends without simply copying them
- Is comfortable receiving feedback and rapidly revising creative work
Helpful Skills
Experience with any of the following is helpful, but definitely not required:
- AI video-generation platforms
- AI image-generation tools
- Adobe Premiere Pro
- After Effects
- Photoshop
- Illustrator
- Canva
- CapCut
- Photography or videography
- Motion graphics
- Animation
- Graphic design
- Scriptwriting
- Generative AI and prompt development
What You'll Gain
You'll have an opportunity to build real-world experience at the intersection of marketing, artificial intelligence, video production, and social media.
You'll gain hands-on experience in:
- Generative AI
- AI video production
- Video editing
- Content strategy
- Social media marketing
- Creative development
- Storytelling
- Product marketing
- Digital advertising
- Marketing analytics
- Working with a professional marketing team
Most importantly, you'll have the opportunity to create real content that is actually published and used by a growing company-not just hypothetical classroom projects.
That means you'll be able to build a portfolio of real-world work.
Position Details
Location: AMD Lasers, West Jordan, Utah Schedule: Approximately 15–25 hours per week Schedule flexibility: We will work around college class schedules Employment: Part-time, Paid
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 CAO Group, Inc, 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 in Demand for This Role
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. Entry-level AI roles across all categories have a median of $110,408.
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.
CAO Group, Inc AI Hiring
CAO Group, Inc has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in West Jordan, UT, US.
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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