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About This Role
TWISTED ALCHEMY
Brand \& Retail Marketing Manager
*Remote \| Part\-Time or Full\-Time \| Immediate Start*
About Twisted Alchemy
We started behind the bar with one goal: make better cocktails easier to execute. What began in hospitality has grown into a fast\-moving premium CPG brand featuring cold\-pressed superfruits, health\-conscious mixers, and a growing retail footprint at Whole Foods Market and beyond.
We are Whole30 Approved, featured on Bar Rescue multiple seasons as THE solution for fresh cocktails, and expanding into new Whole Foods regions in May 2026\. We are a small, nimble team at a real inflection point and everyone on our team takes genuine pride in the work.
About the Role
This role is for someone who has been in the CPG world and knows what it actually takes to launch and grow a brand across multiple channels, not in theory, but in practice.
You understand the Whole Foods shopper. You’ve built retail marketing programs that drive sell\-through, not just sell\-in. You know how to make a demo sing, how to write a coupon offer that moves product, and how to show up at a trade show in a way that builds real relationships. You also understand the hospitality channel, from on\-premise accounts to bartender education and wholesale relationships. You’re creative enough to make things beautiful and commercial enough to make them work.
You’ll report directly to our Co\-Founder/CMO and work across brand, retail, hospitality, experiential, email, and partnership marketing. You’ll collaborate closely with our cross\-functional team across operations, retail, research, social \& influencer, and field marketing.
What You’ll Own
Retail \& Trade Marketing
● Co\-lead retail marketing for our Whole Foods expansion
● Build and maintain retail\-ready assets: sell sheets, shelf talkers, trade decks, promo one\-pagers, distributor tools
● Develop coupon and promotional mechanics in collaboration with our Co\-Founder/CMO
Hospitality \& Wholesale Channel Marketing
● Develop and execute channel marketing strategies for on\-premise accounts, bars, restaurants, and hospitality partners
● Build tools and materials that support the bartender and chef, including recipe guides, back\-of\-house education, and account activation assets
● Manage and nurture wholesale and distributor relationships through targeted marketing support and programming
● Create hospitality\-specific promotional campaigns that drive trial and menu placement
● Leverage our Bar Rescue credibility to open doors and build brand equity in the trade
Shopper Marketing
● Own the path to purchase, from shelf awareness to trial to repeat
● Develop geo\-targeted digital campaign strategy around WFM store locations
● Experience with Aisle, WeStock, or similar natural channel couponing platforms is a strong plus
Email Marketing
● Own email marketing across all key audiences: hospitality partners, retail accounts, DTC consumers, and distributors
● Develop brand awareness, promotional, and educational email campaigns tailored to each channel
● Build and maintain email calendars, templates, and segmentation strategies
● Track performance and optimize for open rates, click\-through, and conversion
Demo \& Experiential
● Collaborate with our Demo Coordinator to elevate the quality and impact of our in\-store demo program
● Develop demo guides, talking points, and brand education tools
● Build brand partnership and co\-marketing opportunities
● Attend key launches, trade shows, and brand events
Brand Creative \& Asset Production
● Design and produce assets across digital, print, retail, hospitality, and experiential touchpoints
● Create visually polished presentations, pitch decks, and partner materials
● Maintain brand consistency, working closely with our Social \& Influencer Specialist
● Direct external photographers, designers, and vendors as needed
Brand Partnerships \& Activations
● Identify and develop co\-marketing opportunities with aligned brands and wellness partners
● Support lifestyle activations including post\-yoga elixir events, pickleball cocktail experiences, and culinary collaborations
● Activate our Bar Rescue credibility across PR, trade, and consumer marketing
Cross\-Channel Flex
● Because we’re a small team, you’ll touch multiple channels as priorities shift
● Bring a solutions\-first mindset: when something needs to get done, you figure out how
What You Bring
Experience \& Background
● 3\-5 years in brand marketing, retail marketing, trade marketing, or hospitality channel marketing, with CPG, food \& beverage, or wellness strongly preferred
● Multichannel experience across retail, hospitality/on\-premise, DTC, and/or wholesale
● Direct experience with a Whole Foods Market launch or expansion, you know how the ecosystem works
● Experience in the WFM produce section is a plus, with understanding of produce buyer relationships and shopper behavior
● Proven track record building retail marketing programs: demos, coupons, promo calendars, and trade tools
● Shopper marketing experience including path to purchase, trial mechanics, and velocity\-building tactics
● Experience with email marketing across multiple audience segments
● Experience with experiential marketing and brand activations
● Background in hospitality, spirits, or wholesale is a meaningful plus
Skills \& Tools
● Proficiency in Adobe Creative Suite (Photoshop, Illustrator, InDesign) and Canva, you produce assets independently
● Excellent writing skills with the ability to adapt to brand voice across channels and audiences
● Strong design sensibility: typography, layout, and brand consistency
● Experience with email marketing platforms (Klaviyo, Mailchimp, or similar)
● Familiarity with Aisle, WeStock, or natural channel couponing platforms is a plus
● Comfortable with project management tools such as Basecamp, Monday.com, Asana, or similar
Mindset
● You’ve worked in a small team and know how to prioritize when everything feels urgent
● You understand both the creative and commercial sides of brand marketing
● You communicate proactively, especially when priorities shift
Bonus Points For
● Experience in the spirits, cocktail, or hospitality industry
● Familiarity with natural channel retail beyond Whole Foods, such as Fresh Market and Erewhon
● Podcast advertising or PR experience
● Wellness, better\-for\-you, or sober curious community experience
● Experience with non\-alc beverage marketing or recipe development
Why This Role
You’ll work directly with a founder, have real ownership, and see your work show up at shelf, at events, in inboxes, and in the hands of people who genuinely love what we make. We move fast, we trust our people, and we build together.
If you’ve been looking for a brand you actually believe in and a team that gives you room to do your best work, we’d love to meet you.
Compensation
Fractional/Contractor: $35–50/hr. This role has the potential to grow into a full\-time position.
How to Apply
Send your resume, a brief note about your CPG, retail, or hospitality marketing background, and any portfolio samples to:
hr@twistedalchemy.com
We review on a rolling basis and move quickly. If this sounds like you, don’t wait.
Pay: $35\.00 \- $50\.00 per hour
Benefits:
- Flexible schedule
Work Location: Remote
Salary Context
This $72K-$104K 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 Twisted Alchemy, 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 ($88K) sits 47% below the category median. Disclosed range: $72K to $104K.
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.
Twisted Alchemy AI Hiring
Twisted Alchemy has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $104K - $104K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
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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