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Apply Now →About This Role
Are You a Creator Who Uses AI to Move Faster?
GoodAutos is building something different.
We are a Kansas City-based automotive company growing toward 8 dealership locations, approximately 600 retail vehicle sales per month, and a rapidly expanding automotive service business.
We are looking for an AI-driven creator, storyteller and brand builder who can help make GoodAutos one of the most recognizable automotive brands in Kansas City.
This is not a traditional marketing job.
This is not a position where you spend your day managing agencies, waiting on creative approvals or making static graphics.
We want someone who can:
Think. Shoot. Create. Edit. Publish. Analyze. Improve. Repeat.
And we want someone who knows how to use AI to multiply their output.
Your MissionBuild attention. Tell our story. Create content people actually want to watch. Make GoodAutos impossible to ignore.
We want GoodAutos to operate like a modern media company that happens to sell and service vehicles.
You will help build the engine behind that vision.
What You Will OwnBrand
You will help shape how GoodAutos looks, sounds and feels across Kansas City.
You will own:
- Brand voice
- Creative direction
- Brand standards
- Campaign creative
- Local storytelling
- Community storytelling
- Store-level creative standards
- Brand consistency across every channel
Content
You will turn the everyday activity inside GoodAutos into content people want to watch.
Content may include:
- Vehicles
- Customer deliveries
- Financing education
- Buying advice
- Automotive service
- Technicians
- Employees
- Leadership
- Customer stories
- Community
- Inventory
- Recon
- Behind-the-scenes operations
- Company culture
- Automotive education
Video
You should be comfortable picking up a camera or phone and creating.
You will:
- Shoot video
- Interview employees
- Direct employees
- Film vehicles
- Film technicians
- Capture customer stories
- Edit video
- Produce Reels
- Produce TikToks
- Produce YouTube Shorts
- Produce longer-form YouTube content
- Create service and educational content
Social
You will help grow the GoodAutos audience across:
- TikTok
- YouTube
- YouTube Shorts
- Google Business Profiles
- Emerging social platforms
We are not looking to simply “post on social.”
We want to build attention, community and demand.
AI Is a Major Part of the Job
GoodAutos is building an AI-first marketing organization.
We expect AI to make this role dramatically more productive.
You should be comfortable using AI for:
- Content ideation
- Scripts
- Hooks
- Headlines
- Captions
- Transcription
- Video clipping
- Editing assistance
- Content repurposing
- Blog creation
- SEO content
- Creative variations
- Campaign concepts
- Content analysis
- Trend research
- Performance insights
Our philosophy is simple:
One great idea should become many pieces of content.
One video might become:
- YouTube content
- Multiple Reels
- TikToks
- Shorts
- Blog content
- Email content
- Google Business content
- Social posts
- Sales enablement content
We want AI handling repetitive production work so you can spend more time creating, experimenting and telling better stories.
Build an Employee Creator Network
You will not be the only person creating content.
GoodAutos employees should become part of the media engine.
You will help salespeople, technicians, leaders and other employees create better content through:
- Scripts
- Prompts
- Content ideas
- Templates
- Coaching
- Training
- Creative standards
Your job is to create a system where great content happens every day across the company.
What Success Looks Like
We care about output and results.
You will be measured on:
- Content produced
- Video produced
- Video views
- Watch time
- Organic reach
- Engagement
- Direct website traffic
- Organic website traffic
- Brand search growth
- Social audience growth
- Employee creator participation
- Content-generated leads
- Content-generated appointments
Who We Want
You may be a great fit if:
- You naturally create content
- You are obsessed with video
- You understand short-form social
- You understand what makes someone stop scrolling
- You can tell stories
- You can shoot
- You can edit
- You understand brand
- You understand social media
- You use AI constantly
- You move fast
- You experiment
- You care about results
- You would rather create than sit in meetings
- You believe great content does not require a huge production budget
A portfolio, social account or examples of previous work will be expected.
You Do NOT Need Automotive Experience
Some of the best candidates may come from:
- Sports
- Entertainment
- Hospitality
- Real estate
- Retail
- Media
- Consumer brands
- Agencies
- Creator businesses
- Startups
We care far more about whether you can:
Create attention. Tell stories. Build a brand. Use AI. Move quickly.
This Role Is Probably Not for You If
- You only want to design graphics
- You do not like shooting video
- You dislike being on location
- You need weeks to create simple content
- You wait for perfect conditions before publishing
- You are uncomfortable experimenting
- You resist AI
- You want to outsource most creative execution
- You do not want your work measured
Why GoodAutos
You will have the opportunity to help build the GoodAutos brand during a major growth period.
You will work closely with executive leadership and Revenue Growth and have significant freedom to:
Create. Experiment. Build. Learn. Scale.
We are not hiring someone simply to manage content.
We are looking for someone who wants to help create a modern automotive media brand powered by AI, video, people and storytelling.
Several years from now, we want you to be able to say:
I helped build that brand.
Pay: $65,000.00 - $95,000.00 per year
Benefits:
- Employee discount
- Flexible schedule
- Health insurance
- Life insurance
- Vision insurance
Work Location: Hybrid remote in Overland Park, KS 66207
Salary Context
This $65K-$95K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At GoodAutos, 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 $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($80K) sits 62% below the category median. Disclosed range: $65K to $95K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
GoodAutos AI Hiring
GoodAutos has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Overland Park, KS, US. Compensation range: $95K - $95K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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