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About This Role
Marketing Manager (Retail Cannabis, Multi\-Location)
Location: West Babylon, NY (Primary) \+ New Jersey
Job Type: Full\-Time, Onsite
Compensation: $60,000 – $68,000 annually
Reports to: Chief Marketing Officer
https://www.joyfulshores.com/
Required Experience (Please Read Before Applying)
- 3\+ years of experience in marketing, digital marketing, or content execution
- Hands\-on experience using AI tools (Claude or similar) in a professional setting
- Experience managing multiple channels (social, website, email, or digital platforms)
About Joyful Shores
Joyful Shores is a licensed adult\-use cannabis dispensary built on a simple idea: cannabis made simple. We are a lifestyle\-forward retail brand operating across New York and New Jersey, powered by a modern retail system, an AI\-driven marketing engine, and a team that takes the work seriously without taking itself too seriously.
Marketing at Joyful Shores is not traditional. It is a purpose\-built, AI\-powered system designed to operate with speed, consistency, and precision across every channel. This role is the person who runs that system.
Role Overview
The Marketing Manager is the execution engine of the Joyful Shores marketing operation. The CMO owns strategy and the marketing plan. This role owns everything that comes after — making the plan run, every day, without fail, across two markets.
On one side of this role, you are managing a sophisticated AI\-powered marketing system: maintaining the website, publishing content, managing loyalty promotions, keeping every online channel current and optimized. On the other side, you are on the ground — coordinating street teams, managing local sign vendors, executing grassroots activations, and building the kind of neighborhood presence that no algorithm can manufacture.
This role requires someone who is intensely interested in AI as a working tool, not as a buzzword. You will use AI systems daily to execute content, manage campaigns, write copy, and operate the marketing machine at a pace and scale that would not be possible otherwise. If you are not actively curious about AI and already using it in your work, this is not the role for you.
You are a self\-starter. You do not need to be managed. You are accountable for your output, not your hours. You take the plan and you run.
Key Responsibilities
1\. AI\-Powered Marketing Engine — Daily Operations
- Operate and maintain the full AI\-powered marketing system across all digital channels for both NY and NJ locations
- Execute the marketing calendar developed by the CMO — on time, on brand, without gaps
- Use AI tools to generate, schedule, and publish content across social, email, and digital platforms at scale
- Monitor channel performance daily; surface insights to the CMO and apply optimizations in real time
- Ensure all AI\-generated content is reviewed, brand\-accurate, and compliant before it goes live
- Stay current on evolving AI marketing tools and proactively identify opportunities to improve the system
2\. Website \& Digital Presence Management
- Own day\-to\-day website maintenance for both locations — menus, promotions, page content, and imagery
- Ensure Dutchie\-powered online menus are accurate, current, and visually consistent at all times
- Manage Leafly storefronts and advertising placements for both locations
- Maintain all digital listings, hours, and location data across platforms (Google, Weedmaps, Leafly, etc.)
- Flag and resolve any digital discrepancies or outdated content immediately
3\. Loyalty, Promotions \& CRM Execution
- Execute all loyalty and promotional campaigns through Dutchie in alignment with the CMO’s plan
- Manage Joyful Perks loyalty program communications, offers, and member\-facing content
- Coordinate promotional timing across digital and in\-store channels to ensure a consistent, seamless experience
- Track promotion performance and report results to the CMO
4\. Content Creation \& Asset Management
- Own the content library for both locations — organized, current, and ready to deploy
- Produce and manage product photography, short\-form video, and lifestyle content using AI\-assisted workflows
- Coordinate with store teams to ensure new inventory is photographed and live\-ready at launch
- Maintain a zero\-tolerance standard for stale, off\-brand, or inaccurate content across any channel
5\. Street\-Level \& Local Marketing
- Execute all local and grassroots marketing efforts — including street team management, flyer distribution, and community activations
- Manage relationships with local vendors including signage, print, and event services
- Coordinate in\-store marketing materials: signage, promotional displays, and branded touchpoints
- Identify and pursue local partnerships, sponsorships, and community engagement opportunities in both markets
- Represent Joyful Shores at off\-site events and activations as needed
- Build a visible, respected local presence in both the New York and New Jersey markets
6\. Brand Partner \& Vendor Coordination
- Execute co\-marketing programs with brand and vendor partners per CMO direction
- Manage partner asset delivery, approvals, and campaign timelines
- Track and report partnership performance
What Success Looks Like
- Every channel — website, social, Leafly, Dutchie, email — is current, accurate, and on\-brand at all times
- The marketing calendar runs on schedule with zero missed beats
- Local presence in both markets is visible, consistent, and growing
- AI tools are being used to their full capacity — not as a shortcut, but as a force multiplier
- The CMO spends zero time chasing execution; this person handles it
Qualifications
Experience
- 3–5 years of experience in marketing, content creation, digital marketing, or brand management
- Demonstrated experience managing multi\-channel campaigns independently, from execution to reporting
- Hands\-on experience with AI marketing tools in a professional context — required, not preferred
- Multi\-location or multi\-market experience a strong plus
- Cannabis industry experience a plus but not required
Skills \& Competencies
- Deep, working fluency with AI tools — you use them every day and know how to get real results from them
- Strong visual standards and content creation skills: photography, short\-form video, basic editing
- Systems\-oriented: you build and maintain workflows, not just one\-off tasks
- Comfortable with data — able to pull, interpret, and act on performance metrics without being asked
- Familiarity with Dutchie, Leafly, or cannabis retail platforms is a strong plus
- Organized and responsive; can manage competing priorities across two stores without losing details
- Comfortable operating both behind a screen and on the street — this role does both
Who You Are
- An extreme self\-starter. You do not wait to be told what to do next.
- Accountable for output, not effort. You measure yourself by results.
- Intensely interested in AI as a professional tool — you are building expertise here, not experimenting casually
- Organized enough to manage a multi\-location marketing operation and scrappy enough to hand out flyers on a Saturday
- Excited about building a real brand in real communities — not just pushing content into a void
- Reliable, consistent, and not precious about doing whatever the work requires
Working Conditions
- Regular travel between NY and NJ locations required
- Some evening and weekend availability required for events, activations, and store launches
- Primarily based out of the West Babylon, NY location
Growth Opportunity
This is a foundational hire at a brand being built from the ground up. Clear path toward:
- Director of Marketing
- VP of Marketing \& Brand
- Multi\-location Marketing \& Brand Operations leadership
Candidates should be able to reliably commute to Babylon, NY, as this role requires consistent onsite presence.
Equal Employment Opportunity Statement
Joyful Shores is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, creed, national origin, ancestry, citizenship, sex, gender identity or expression, sexual orientation, age, disability, marital status, veteran status, genetic information, or any other protected classification under applicable federal, state, or local laws. All employment decisions are based on qualifications, merit, and business needs.
Pay: $60,000\.00 \- $68,000\.00 per year
Benefits:
- Paid time off
Application Question(s):
- Are you 21 years of age or older?
- Are you able to work onsite in West Babylon, NY and within a 30 minute commute to work?
- Tell us about your experience using AI marketing tools.
- Do you have at least 3 years of experience in marketing, content creation, digital marketing or brand management?
Work Location: In person
Salary Context
This $60K-$68K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Joyful Shores, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($64K) sits 62% below the category median. Disclosed range: $60K to $68K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Joyful Shores AI Hiring
Joyful Shores has 5 open AI roles right now. They're hiring across AI/ML Engineer. Based in West Babylon, NY, US. Compensation range: $45K - $90K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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