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About This Role
POSITION SUMMARY:
The Email Marketing Manager will be experienced in Salesforce Marketing Cloud (or comparable marketing platform), goal\-oriented, and driven by results. This role will be responsible for development and delivery of emails, SMS, and Push campaigns from end\-to\-end journeys. The incumbent in this role will partner with internal stakeholders to develop data\-driven strategies and increase KPIs. The ideal candidate will thrive in a fast\-paced team environment and possess a high aptitude to learn.
ESSENTIAL DUTIES:
Lead, develop and manage a team of email marketers
Primarily responsible for development and execution of email, SMS, and Push communications from end\-to\-end
Drive the organization’s reach through awareness, consideration, acquisition, retention, transactional, and onboarding initiatives
Works closely with cross\-functional teams to create, execute, and measure integrated email programs to drive the business
Partner with marketing leads to develop list criteria/segmentation requirements for campaigns to reduce operational timelines and increase efficiency
Refine segmentation strategies and enhance targeting based on data driven results
Conceptualize and initiate tests to continually improve key metrics across programs
Assist in the development of analytics dashboards and analyze campaign metrics to drive day\-to\-day business decisions and determine future initiatives
Identify and deliver process improvements to increase speed to market
Work closely with IT to resolve issues, data flows or other discrepancies
Managerial Responsibilities
Leadership and Performance Management:
Partner with your supervisor to determine team objectives, ensuring they align with and support the achievement of organizational goals.
Lead the annual goal\-setting process with direct report(s), collaborating to identify goals that support achieving organizational objectives. Ensure goals are added to the HRIS system by due dates, and all timeframes of the performance cycle are followed by your team.
Support, guide, and manage the development and performance of direct report(s) through regular one\-on\-one sessions, mid\-year and annual performance review processes. Proactively create development plans that align with the organization’s operational needs.
Provide clear communication to direct report(s). Ensure your direct report(s) understand the breadth and depth of their position, performance expectations, deliverables, team relations, etc.
Identify, investigate, and address performance issues and/or team member relations issues in real\-time, ensuring timely, clear, and accurate documentation of the problem. Proactively seek guidance from next\-level management when attempts to resolve issues do not yield timely, acceptable, and sustainable results.
Identify skills gaps necessary to accomplish tasks, utilize and leverage tools to the maximum extent possible, and implement individual and cross\-training plans to close gaps.
Workforce Planning and Team Management:
Actively participate in the recruiting process for approved hires. This includes reviewing and updating position descriptions before recruiting, as well as candidate selection and interviews.
New employee onboarding plan development. Development of a 12\-month plan to support the strategic development of a newly hired or promoted individual.
Assign tasks, manage workloads and schedules, and allocate resources to optimize productivity and ensure deadlines are met. Evaluate workflows inter and intra departmentally to level work processes and ensure equal distribution of work between similar roles.
Compliance and Policy Enforcement:
Knowledgeable of organizational policies, employment laws, and regulations, and ensuring compliance of these within your team and among your direct report(s).
Maintain unwavering confidentiality, discretion, and accuracy regarding personnel records related to employee performance, attendance, and disciplinary actions.
\*\*Although this job description aims to capture the majority of the position duties, other duties may be assigned based on business and departmental needs.
REQUIRED QUALIFICATIONS:
Bachelor's degree or equivalent work experience
5\+ years related experience
Experience building content, creating journey automations, and audience definition
Ability to balance a strong management presence with a high level of approachability, encouraging and eliciting associate feedback and interaction
Ability to innovate and drive efficiencies that increase impact
Excellent project management skills
Ability to manage both creative requirements and operational needs
PREFERRED QUALIFICATIONS:
1\+ years Salesforce (or comparable platform) administrator experience
Salesforce (or comparable platform) Certified Marketing Cloud Email Specialist Certification
Salesforce Certified Administrator Certification
Salesforce Certified Marketing Cloud Consultant Certification
Experience with enterprise analytics platforms such as Google and SQL
WORKING CONDITIONS:
This position works in an office setting.
Typical working hours are 8:30 am – 5 pm, Monday through Friday, with a one\-hour lunch break.
Generally, a climate\-controlled environment with occasional exposure to outdoor weather conditions when attending aviation\-related events, including exposure to higher altitudes and confined spaces, if in a general aviation aircraft.
This position may require up to 5% travel. Potential travel may include local community or networking events, as well as industry\-related seminars. Travel is by aircraft (general aviation and commercial) and by road or public transit.
PHYSICAL DEMANDS:
The physical demands of this position are typical of a standard office environment. While performing the duties of this job, the employee will regularly be required to:
Sit for extended periods while working at a computer or attending meetings.
Use hands and fingers to operate a computer keyboard, mouse, and other office equipment.
Communicate effectively via email, phone, and in person, which requires clear speech, hearing, and vision.
Occasionally lift or move items weighing up to 15 pounds, such as boxes of materials or equipment.
Occasionally stand, walk, and reach with hands and arms during the course of normal office activities.
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 accommodation will be made to enable individuals with disabilities to perform the essential functions.
ADDITIONAL INFORMATION:
This position is located at AOPA’s Frederick, MD, office.
The salary range for this position is: $70,000 \- $76,000, depending on education and experience.
BENEFIT INFORMATION:
Flight Training (earn your Private Pilot License for free) \& Annual Flight Proficiency Program (so you can keep flying and remain proficient)
Medical, Dental, and Vision insurance is available for employees and their dependents the 1st of the month following their start date
Flexible Spending Plans
Health Savings Plan with employer contribution (for eligible participants)
401(k) Retirement Plan with a company match, and annual discretionary supplemental employer contribution
Company paid Short and Long\-term Disability Insurance
Company paid Life Insurance and AD\&D insurance with the option to buy up
Paid Time Off (PTO): 17 days accrued during first year (accruals increase based on tenure)
Paid Holidays: 12 holidays
Personal days: 3 (prorated based on hire date)
Volunteer day: 1 (prorated based on hire date)
Work From Home Fridays
Paid Parental Leave
AOPA Membership
Employee Assistance Program
Wellness Program (earn medical insurance premium discounts)
Gym Reimbursement Program
Supplemental insurance options (critical illness, accident, hospital indemnity)
Tuition Reimbursement Program
Discount on AOPA swag
Business casual dress code
Free coffee, tea, hot cocoa
Salary Context
This $70K-$76K 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 AOPA Holdings Corporation, 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: $70K to $76K.
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.
AOPA Holdings Corporation AI Hiring
AOPA Holdings Corporation has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Frederick, MD, US. Compensation range: $76K - $76K.
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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