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About This Role
Location: Remote
Job Type: Contractor
Capacity: 20 Hours / Week \- Monday to Friday
To the future Greenhouse Copywriter and Email Marketing Coordinator
Are you a detail\-oriented, proactive Email Marketing professional looking to join a fast\-growing marketing agency?
Are you someone who thrives in a high\-energy environment and is passionate about building relationships?
Do you want to work with a dynamic team of retention marketing professionals who collaborate with clients across various industries to help those clients achieve their marketing objectives?
If that’s a third YES, this is the role for you.
About us:
We are a value driven company on a mission to help brands grow and scale with confidence.
Our mission is to hire, develop and retain the best marketing talent and make that talent available to brands so that they grow and scale with confidence.
Our team is our most valuable asset. As a member of our team, you'll have the opportunity to work with a group of talented thinkers, dreamers, and doers who move the industry forward with fresh ideas and excellent service.
So, if you're interested in working remotely with a fun, talented, and fast\-growing team, then come join us at The Greenhouse! Let's break boundaries and make an impact together, one email/SMS strategy at a time.
What you'll be doing:
As a copywriter and email marketing coordinator you will work alongside the Retention Marketing Manager to help manage 6\-10 email and SMS marketing brands. This includes writing clear and error\-free email and SMS campaigns, proofreading, project management, assisting with client relations and communication, and helping to execute campaign strategies, flow/automation strategies. Your goal is to be the right hand to the Retention Marketing Manager and assist them as needed. During this role, you'll have the opportunity to work directly with the Director of Lifecycle, the Creative team, and our Greenhouse partners on fun retention and creative projects.
What We're Looking For:
This role requires a proactive and results\-driven person with a strong understanding of marketing principles, relationship management, and project coordination. The ideal candidate will have excellent communication skills, a keen ability to manage expectations, and a track record of successfully executing marketing campaigns that drive client satisfaction and business growth.
The ideal person for this role would be someone who is:
- A self\-starter with a strong work ethic and passion for marketing and e\-commerce
- A high performer that holds themselves accountable to high standards
Requirements:
- Operate within company hours: Monday to Friday from 9am to 5pm ET / PT.
- Attend client meetings alongside the Retention Marketing Manager (PST and EST time zones)
- 1\-2 yrs experience in copywriting and email marketing, lifecycle, or retention roles
- Maintains a high level of professionalism in client\-facing interactions, fostering trust and confidence while ensuring satisfaction and delivering results
- Strong written and verbal communication skills – with understanding of situational best practices
- Must have an eye for creativity and details
- 1\-2 years of e\-commerce marketing experience
- 1\-2 years of experience with Klaviyo
Nice to have:
- Klaviyo Product Certification
- Experience working in an E\-commerce or Digital Marketing agency
- Experience with Attentive or other mobile platforms
- Experience managing an email, SMS
- Experience working with 6\-7 figure e\-commerce brands
- Knowledge of DTC customer lifecycle and retention marketing
Our non\-negotiables (Must Read)
If you can commit to and live with the following principles, then you are the type of person who will be successful and help our company thrive.
If you feel this level of engagement is not right for you or that you’re not willing or able to participate with us at this level, we are not a good fit for you. Our expectation is that you will take the steps necessary to do what you say you are going to do and be accountable for your actions. In other words, live “Above the Line.”
We understand that not every person is ready for this level of performance, and we appreciate the honesty of those who decide this is not the right place for them. On the other hand, you would make an ideal candidate to join our company if you are willing to commit to the following Above the Line principles:
- Accountability: See It, Own It, Solve It, Do It
- Become part of the solution and act now
- Respect for others and their feelings
- Ask the question: “What else can I do?”
- Ask the questions: “What coaching do you have for me?” and “What can I do better?
- Reject average
- Show others that you care
Next Step:
Now, if you think you are the ideal candidate for this role, please visit https://www.growwithgreenhouse.com/job/email\-sms\-marketing\-coordinator to submit your application directly to The Greenhouse hiring team
Job Types: Part\-time, Contract
Pay: $20\.00 per hour
Application Question(s):
- To be considered for an interview, you must apply from the company website.
Did you send your application from The Greenhouse website?
Work Location: Remote
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 The Greenhouse Marketing, 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.
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.
The Greenhouse Marketing AI Hiring
The Greenhouse Marketing has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US.
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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