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About This Role
DaySmart supercharges experience-based businesses with innovative, industry-specific software services that power customer and revenue growth. With thousands of partners worldwide and dozens of industry awards, we provide best-in-class solutions that help our customers grow their businesses.
About Slick
Slick is the appointment and payment software that salon owners actually love. Born from Founders Factory and built in collaboration with L'Oreal, we're changing how hair and beauty businesses manage bookings, payments, stock, and the admin that gets in the way of creativity. Around ten thousand businesses run on Slick. In the UK we're established and well known. In the US we're almost entirely unknown, and that's the part that should interest you.
Note: We're looking for candidates based in or able to work Eastern Time hours. This role partners closely with our UK team, and Eastern Time overlap is essential for effective collaboration.
The Opportunity
We're looking for an AI-enabled Growth Marketing Manager to build Slick's presence in the US. You'll sit in the Beauty BU and report directly to our Head of Marketing, who you will partner with across many growth initiatives.
The role isn't optimizing a funnel that already works, it's finding where salon owners are already paying attention and getting Slick in front of them, then making sure the page they land on earns the click.
This is a broad role and a hands-on one. You'll be making things and getting them in front of people, and you'll see them live the same week.
We're a startup inside a bigger company, however you do have real support in the places that usually eat a growth marketer's week. You're not buying media or living inside the Meta or Google Ads accounts, and you're not making the creative. But you'll also stretch past what's traditionally growth marketing. Some weeks that means pitching a trade publication or chasing a podcast booking. Some weeks it means helping our product marketer get a launch out the door, or picking up a partnership conversation because you're the one who spotted it.
That breadth is only workable because of how the job gets done. If you already use AI to compress research, drafting, production and analysis into a fraction of the time they used to take, this scope is exciting rather than impossible. That's the honest bar, and it's why the title says what it says.
What You'll Own
You own one question: where are US salon owners already paying attention, and how do we show
up there and convert? That means:
- Develop the campaign concepts and creative briefs behind our paid programs, then build and test the landing pages traffic arrives on. We have an agency on Meta and Google, so you're not buying media, you're deciding what runs, and you own conversion rate on every page where we point spend.
- Own the third-party citation work that gets Slick cited by AI answer engines. It's the same outreach muscle as press, pointed at a different target, and it's becoming one of the highest-leverage things a growth marketer can do.
- Produce ‘question shaped’ content built for how salon owners search now, across Google and AI assistants, and measure whether it landed.
- Be our voice in community groups.
- Build and launch nurture email sequences with support from marketing and central services teams.
- Get our customer referral program off the ground.
- Partner with our social manager on US campaign concepts and American context.
- Keep the view of what's shipping, so the whole team knows what's live and what's next.
- You'll be measured on qualified volume into the US funnel, conversion rate on every page we point paid spend at, and whether Slick starts showing up in the places US salon owners look, including AI answers.
About You
You've spent 4+ years across growth, campaign or content marketing, ideally at a software
company selling to small business owners. If you came up at an agency running paid, content and
outreach across several accounts at once, we'd very much like to talk.
We're particularly excited if you've worked in:
- Beauty, wellness, or personal care software
- Appointments, scheduling, home services or restaurant tech, or anywhere the buyer is an owner-operator
Beyond that, what matters:
- You ship. Your portfolio has live links in it. Pages you built, campaigns you ran, things a customer actually saw. Not a folder of decks.
- You move fast with AI tooling, and it's central to how you work rather than a novelty. Claude cowork/code, NotebookLM, whatever you've landed on. You've built workflows you actually run every week, and ideally you've made something with it that didn't exist before: a page, a tool, an automation, a video. This is the single thing that makes a role this broad workable, so we'll want to hear specifics.
- If you can make things yourself, you'll have room to. Video, design, landing pages, interactive tools, whatever your skillset actually covers. Some of our strongest assets exist because one person sat down and built the thing rather than writing a brief for it, and we'd always rather you do that than wait in a queue.
- You write well and quickly. Landing page copy, ad copy, a pitch email, a community comment that doesn't read like marketing.
- You know how American small business owners really talk, because you'll be spending time in rooms full of them.
- You're fine with nobody having heard of us yet. Creating demand is a different job from capturing it, and you know the difference.
Why You'll Love This
The work goes live. There's no large committee between you and the market and no queue to route a landing page through. You have autonomy and you'll see the thing you made in the wild days after you made it.
The scope is broad for one role, and it's real ownership rather than a support function. And the market is genuinely good. Salon owners are underserved by their software and they know it. You'll also have a mature product and thousands of real customers in the UK to point at, which makes the US story a lot easier to tell than starting from zero.
Salary
- The salary for this role is $85,000-95,000 per year. Pay is based on several factors including but not limited to education, work experience, certifications, internal equity, etc.
What We Offer
- Competitive salary and benefits including medical, dental, vision, HSA, FSA, and more!
- 401k plan with company match on your contributions.
- Open PTO and a generous paid holiday schedule.
- Supportive work environment with the flexibility to work where/how you want – in-office, remote, or hybrid.
- Opportunities to ensure you are always learning and growing.
How You Will Work
This will be a US based position. We offer flexible work arrangements including fully remote, in person or hybrid opportunities. For those looking to work in person, we have physical offices in the following cities:
- Ann Arbor, MI
- Wayne, PA
- Austin, TX
Many DaySmart employees primarily work from home, and our teams are structured to operate efficiently in a distributed environment. While we don’t always share a physical office, we work together closely through remote collaboration practices.
We maintain a highly collaborative culture and expect all employees to actively participate in meetings, discussions, and team interactions. This includes joining scheduled video calls with cameras on, contributing to conversations, and being fully present.
We believe that strong communication and visual connection are essential to maintaining alignment, accountability, and trust across our teams. At DaySmart, working remotely comes with the responsibility to show up, engage, and collaborate with intention.
Your safety is important to us!
We’ve recently identified an increase in fraudulent activity targeting individuals who have applied to positions at DaySmart. Please note that any legitimate communication regarding your application will come either from an official DaySmart email address (ending in @daysmart.com) or directly through our Applicant Tracking System.
Please refer to DaySmart Privacy Policy to learn more about how we are committed to respecting your privacy and the security of your personal information.
DaySmart is committed to creating a diverse employee environment and is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, disability, age, or veteran status.
Salary Context
This $85K-$95K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At DaySmart Software, 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 $212,000 based on 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($90K) sits 58% below the category median. Disclosed range: $85K to $95K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
DaySmart Software AI Hiring
DaySmart Software has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $95K - $95K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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