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About This Role
Are you a strategic marketer who knows how to turn email into a high\-impact growth channel?
Do you enjoy building and optimizing campaigns that drive engagement, conversion, and long\-term customer value?
We’re looking for a Senior Email Marketing Specialist to help scale and evolve our email marketing efforts as we continue to grow. In this role, you’ll take ownership of key initiatives across strategy, segmentation, automation, and performance—helping us deliver more personalized, effective communication across the entire customer journey.
This is a high\-impact opportunity for someone who thrives on data, testing, and continuous optimization, and wants to play a meaningful role in shaping how email contributes to overall business growth.
Why Join Us?
We're a rapidly growing digital pharmacy where you will have the opportunity to contribute to our joint success on a daily basis. We value new ideas, creativity, and productivity. We like people who are passionate about their roles and people who like to grow and change as the company evolves.
At AmeriPharma, you'll have access to:
- Competitive pay and generous compensation structures
- Full benefits package including medical, dental, vision, and life that fits your lifestyle and goals
- Employee assistance program to assist with mental health, legal questions, financial counseling, and more
- 401k program
- Comprehensive PTO and sick leave options
- Opportunities for growth and advancement
- Casual Fridays
Role Details
Reports to: Digital Marketing Operations Manager
Starting Salary Range: $80,000 \- $95,000 / Annually
Hours: Monday\-Friday, 8\-hour shift between 9:00 AM\-5:30 PM
Job Summary
The Senior Email Marketing Specialist will lead the strategy and execution of email marketing initiatives that drive engagement, conversion, and customer growth. This role is responsible for developing targeted, personalized campaigns across the customer lifecycle—from lead nurturing to retention—using data\-driven segmentation and automation.
You’ll manage the full email marketing process, including campaign planning, workflows, list growth and management, testing, reporting, and ongoing optimization. Working cross\-functionally with the broader marketing team, you’ll help identify key customer touchpoints and ensure email is effectively integrated into the overall customer journey.
Duties and Responsibilities:
- Develop and execute email marketing strategies for each customer persona, leveraging analytics to inform segmentation and personalization strategies
- Drive email list growth through creative opt\-in strategies including partnering with key organizations
- Build and optimize email content segmentation and personalization strategies by leveraging analytics on user behavior and activity.
- Lead planning and oversee execution for email marketing calendar of email campaigns, including content\-focused emails, automation, triggers, and more
- Oversee the content of campaigns, including proofreading copy, design, mobile optimization, personalization, and more
- Coordinate with design and copywriting teams to ensure that campaigns are visually appealing, mobile\-friendly, and well\-written
- Drive execution of new triggers, automation and personalization tactics.
- Develop an ongoing testing strategy for variables such as template, content, calls\-to\-action, timing and frequency.
- Produce weekly reports on email performance and provide insights for optimization. Use reports to analyze customer data to maximize campaign performance.
- Research and recommend appropriate email marketing tools and software.
- Keep up\-to\-date with latest best practices, strategies, and industry standards.
- Ensure email compliance (including CCPA) and spam regulations (CAN\-SPAM).
- Develop and manage internal company communications, including email announcements and updates to ensure effective internal engagement.
- Collaborate with cross\-functional teams to ensure operational emails align with overall marketing strategies and enhance the customer experience.
- Other duties as assigned.
Required Qualifications
- 5\+ years of experience in email marketing, with a proven track record of growing engagement, conversion, and revenue growth
- Proven ability to develop and execute email marketing strategy, including segmentation, lifecycle marketing, and campaign planning
- Strong understanding of customer journeys and how to use emails to support acquisition, activation, retention, and re\-engagement
- Understanding of email deliverability and sender reputation best practices
- Strong attention to detail and ability to manage multiple projects simultaneously
- Strong communication and collaboration skills, with the ability to work effectively with cross\-functional teams
- Experience with lead generation and lead nurturing strategy, including building and optimizing automated flows
- Strong analytical mindset, with experience using data to inform testing, optimization, and strategic decisions
- Experience with email marketing platforms and analytics/reporting tools
Preferred Qualifications
- Bachelor's degree in marketing, communications, or a related field
- Proficiency in ActiveCampaign strongly preferred
- Experience with CRM systems like HighLevel strongly preferred
- Strong design skills and experience with HTML and CSS responsive email templates
- Experience with A/B testing and optimizing email campaigns
- Knowledge of email compliance regulations (e.g., CAN\-SPAM, CCPA)
- Experience with marketing automation tools (e.g., Marketo, HubSpot)
- Proven ability to drive results and grow engagement and revenue through email marketing strategies.
AmeriPharma’s Mission Statement
Our goal is to achieve superior clinical and economic outcomes while maintaining the utmost compassion and care for our patients. It is our joint and individual responsibility daily to demonstrate to outpatients, prescribers, colleagues, and others that We Care!
Physical Requirements
The 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. While performing the duties of this job, the employee is continuously required to sit and talk or hear. The employee is occasionally required to stand; walk; use hands to finger, handle, or feel objects, tools, or controls; reach with hands and arms; and stoop, kneel, crouch or crawl. The employee must regularly lift and/or move up to 20 pounds and occasionally lift/or move up to 30 pounds. Specific vision abilities required by this job include close vision, peripheral vision, depth perception and the ability to adjust focus.
EEO Statement
The above statements are intended to describe the work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties and skills required. The duties and responsibilities of this position are subject to change and other duties may be assigned or removed at any time. AmeriPharma values diversity in its workforce and is proud to be an AAP/EEO employer. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, age, protected veteran status, or based on disability or any other legally protected class.
Salary Context
This $80K-$100K 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 AmeriPharma, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($90K) sits 46% below the category median. Disclosed range: $80K to $100K.
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.
AmeriPharma AI Hiring
AmeriPharma has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Laguna Hills, CA, US. Compensation range: $100K - $100K.
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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