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About This Role
Job Overview
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We are seeking an experienced Marketing Manager to lead and execute all marketing initiatives for three rooftop automotive dealerships, overseeing strategy and performance across all digital and traditional marketing platforms. This role is responsible for developing innovative sales and service campaigns that attract today's automotive consumers, drive showroom traffic, and generate measurable business growth. The ideal candidate will leverage the latest marketing technologies, data analytics, AI\-driven tools, and creative solutions to deliver impactful campaigns while providing comprehensive reporting and performance insights across current and emerging platforms. This is a full\-time, onsite position Monday through Friday, requiring strong leadership, collaboration, and a proven track record of success in automotive or multi\-location marketing environments.
Salary Range: $60,000\.00 \- $150,000\.00 per year
Benefits
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Annual Base Salary \+ Bonus Opportunities
Paid Time Off (PTO)
Health Insurance
Dental Insurance
Vision Insurance
Mon\-Fri Schedule
Career Growth Opportunities
Retirement Plan
Evenings Off
Requirements
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\*\*Requirements \& Qualifications:\*\*
- Bachelor's degree in Marketing, Business, Communications, Advertising, or a related field; Master's degree preferred.
- Minimum of 5\-7 years of progressive marketing experience, with at least 3 years in a leadership role managing multi\-location or multi\-brand marketing operations.
- Automotive marketing experience strongly preferred, with a demonstrated understanding of dealership operations, sales processes, fixed operations, inventory management, and OEM marketing programs.
- Proven track record of developing and executing successful marketing campaigns that drive measurable increases in vehicle sales, service traffic, lead generation, and customer retention.
- Advanced knowledge of digital marketing platforms, including Google Ads, Meta (Facebook/Instagram), YouTube, SEO, SEM, display advertising, email marketing, CRM marketing, and reputation management.
- Experience utilizing AI\-powered marketing tools, automation platforms, customer data platforms, and advanced analytics solutions to improve campaign performance and efficiency.
- Strong proficiency in Google Analytics, Looker Studio, CRM reporting systems, and other business intelligence tools used for marketing attribution and performance measurement.
- Exceptional analytical skills with the ability to interpret data, identify trends, develop insights, and present executive\-level reports and recommendations.
- Demonstrated experience managing substantial marketing budgets and maximizing return on investment through strategic planning and resource allocation.
- Strong project management skills with the ability to manage multiple campaigns, deadlines, vendors, and dealership priorities simultaneously.
- Experience overseeing creative development including digital content, video production, graphic design, copywriting, and brand management.
- Excellent communication, leadership, and interpersonal skills with the ability to collaborate effectively across departments and influence organizational decision\-making.
- High level of proficiency in Microsoft Office Suite, marketing automation platforms, CRM systems, and emerging marketing technologies.
- Self\-motivated, highly organized, and results\-driven with a commitment to continuous improvement and innovation.
- Ability to work onsite Monday through Friday and actively engage with dealership leadership, sales teams, and service departments to support business objectives.
- Strong understanding of consumer behavior, market trends, and evolving automotive retail technologies.
- Valid driver's license and ability to travel between dealership locations as needed.
\*\*Preferred Qualifications:\*\*
- Experience managing marketing for multiple dealership rooftops or large retail organizations.
- Certifications in Google Ads, Google Analytics, Meta Advertising, HubSpot, or other recognized marketing platforms.
- Experience with automotive CRM systems, inventory marketing platforms, and digital retailing technologies.
- Knowledge of AI content creation, predictive analytics, marketing automation, and customer journey optimization.
- Demonstrated success building in\-house marketing processes and reducing reliance on outside agencies through strategic use of technology and automation.
Responsibilities
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\*\*Responsibilities:\*\*
- Develop, manage, and optimize comprehensive marketing strategies for three rooftop automotive dealerships, ensuring alignment with organizational sales and service objectives.
- Create, execute, and monitor multi\-channel advertising campaigns across digital, social media, search, email, video, radio, television, direct mail, and other emerging marketing platforms.
- Drive customer acquisition initiatives that increase vehicle sales, service appointments, and overall dealership traffic through targeted and data\-driven marketing efforts.
- Oversee dealership websites, SEO, SEM, online reputation management, and digital lead generation strategies to maximize visibility and conversion performance.
- Manage relationships with advertising agencies, media partners, OEM marketing programs, technology vendors, and other external marketing resources.
- Utilize advanced analytics, AI\-powered marketing tools, and reporting platforms to track campaign effectiveness, identify trends, and provide actionable insights to leadership.
- Develop compelling creative content, promotional messaging, and branding initiatives that maintain consistency across all dealership locations and customer touchpoints.
- Monitor and manage marketing budgets, ensuring efficient allocation of resources and maximizing return on investment (ROI).
- Analyze market conditions, competitor activities, consumer behavior, and industry trends to identify new opportunities and maintain a competitive advantage.
- Collaborate with dealership leadership, sales managers, fixed operations teams, and vendor partners to align marketing efforts with operational goals and inventory strategies.
- Lead the planning and execution of dealership events, seasonal promotions, service campaigns, and community engagement initiatives.
- Establish key performance indicators (KPIs) and provide detailed reporting on campaign performance, lead generation, customer acquisition costs, and overall marketing effectiveness.
- Implement and manage customer retention and loyalty marketing programs designed to increase repeat sales and service business.
- Stay current on emerging marketing technologies, AI applications, digital trends, and automotive industry best practices to continuously improve marketing performance and innovation.
- Ensure compliance with OEM brand standards, advertising regulations, and company policies across all marketing activities.
About Us
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City Automall is a dynamic automotive dealership specializing in new Ford \& Chevrolet, and quality used vehicles. We're driven by a commitment to exceptional customer service, fostering a transparent, family\-like culture. Join our energetic team dedicated to empowering customers and delivering top\-tier sales, finance, and service experiences. Accelerate your career with us!
Salary Context
This $60K-$150K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $181K across 1996 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 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At City Automall, 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 $178,940 based on 11,900 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($105K) sits 41% below the category median. Disclosed range: $60K to $150K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
City Automall AI Hiring
City Automall has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Fort Wayne, IN, US. Compensation range: $150K - $150K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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