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About This Role
Job Title: Email Marketing Automation Specialist
Department: Marketing
Reports To: Director of Marketing
Status: Full\-time, Exempt
Annual Budget Managed: $25,000
Fundraising Impact: $1 million
Location: Remote/Hybrid; Burlington, Canada or Byron Center, MI
Salary Level: K
USD: $68,347 \- $76, 890
CAD: $70,461 \- $79,268
- Please be advised that while this role is advertised in both Canada and the United States, it represents *a single* *position. Only one (1\) candidate will be selected for hire, with the final work location to be* determined based on the successful candidate's residence and organizational requirements.
PURPOSE:
The Email Marketing Automation Specialist develops, executes, and optimizes World Renew's email marketing strategy to support donor acquisition, fundraising, and engagement goals. This position is responsible for building and managing automated campaigns, maintaining the marketing automation platform, and leveraging data insights to enhance lead generation, donor nurturing, and overall engagement.
Working closely with the Director of Marketing and cross\-departmental teams, the specialist applies best practices in email strategy, list management, segmentation, testing, and automation. The role requires a blend of creativity and technical expertise, with an emphasis on continual testing, analysis, and optimization to improve results and audience connection.
*We do not discriminate based on disability, culture, ethnicity, or gender, and welcome and encourage people from diverse backgrounds to apply.*
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Develop and implement email marketing campaigns that align with organizational and team goals, adapting tone and messaging appropriately for diverse cultural contexts.
- Design, manage, and optimize automated workflows and nurture sequences, including onboarding and engagement for new leads.
- Utilize and continually refine dynamic content to strengthen donor engagement and increase fundraising outcomes.
- Collaborate with Marketing team members to plan and produce engaging, personalized email content that supports donor relationships and organizational priorities.
- Segment email lists to deliver targeted, relevant, and timely messages to specific audience groups.
- Conduct A/B testing and analyze performance metrics to inform ongoing optimization of campaigns.
- Ensure compliance with email marketing and privacy regulations in both Canada and the U.S. Maintain data accuracy and collaborate with CRM/database teams to ensure effective integration with Salesforce. Leverage CRM data for enhanced segmentation, personalization, and campaign tracking.
- Monitor deliverability and campaign performance, addressing technical issues promptly to ensure optimal platform functionality.
- Prepare and present reports on key metrics such as open rates, click\-through rates, conversions, and donor engagement trends.
- Manage and maintain subscriber lists to ensure data integrity, accuracy, and list hygiene.
- Perform other duties as assigned.
SUPERVISORY RESPONSIBILITIES:
None
KNOWLEDGE, SKILLS, ABILITIES REQUIRED:
- Able to respect and support the mission, vision and values of World Renew.
- Demonstrated commitment to Christ and be able to recognize this position as one that contributes to the work of His Kingdom.
- Demonstrated commitment to contribute to and promote a work environment that values diversity, inclusion and equity.
- Committed to working towards gender equality, equity and justice in all aspects of our programming, plans, policies and organizational structure.
- Proven experience using marketing automation/email platforms such as Pardot/Account Engagement, MailChimp or HubSpot at advanced level preferred.
- Proficiency in Salesforce CRM preferred.
- Strong interpersonal and communication skills, with the ability to collaborate effectively across teams.
- Proficiency in HTML and familiarity with creative tools such as Adobe Creative Suite or Canva (preferred).
- Familiarity with online fundraising and engagement platforms (eg SurveyMonkey, Click \& Pledge, WP Forms) a plus.
- Data\-driven mindset with experience in reporting, analytics, and campaign optimization.
- Attention to detail, organizational skills, and ability to manage timelines in a fast\-paced environment.
- Ability to travel once annually for a three\-day team meeting.
EDUCATION \& EXPERIENCE:
- Bachelor's degree in Marketing, Communications, or related field (or equivalent experience).
- At least 3\- 5 years of experience in digital marketing; and minimum of three years of experience in email marketing automation preferred
LANGUAGE SKILLS:
Must be proficient in English (written and verbal).
WORK ENVIRONMENT, PHYSICAL AND OTHER DEMANDS:
The work environment encountered and physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This position requires:
- Must be able to look at a computer screen for several hours at a time.
- Must be able to sit for extended periods.
- Must be able to make repetitive motions with hands and fingers for extended periods.
- Work is performed in a remote or hybrid office setting with minimal exposure to adverse conditions.
World Renew requires permanent work authorization at time of hire. With World Renew's commitment to Core Humanitarian Standard and Safeguarding responsibilities, as part of the recruitment process, a successful candidate can expect to go through a thorough background check. Please note that the tentative application deadline for this position will be EOD April 23, 2026, for External Applicants and Internal Applicants, closing date depending on application volume. We encourage all interested candidates to apply before this deadline as we move candidates through our hiring process on a continuous basis
Salary Context
This $68K-$79K 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 World Renew, 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 ($73K) sits 56% below the category median. Disclosed range: $68K to $79K.
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.
World Renew AI Hiring
World Renew has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Byron Center, MI, US. Compensation range: $79K - $79K.
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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