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About This Role
The mission of Jazz at Lincoln Center, Inc. (“JALC”) is to entertain, enrich and expand a global community for jazz through performance, education, and advocacy. From college students to young stars, from working professionals to celebrated masters, we present quality jazz for an ever\-increasing audience in an unprecedented range of activities and a variety of venues. We are dedicated to lifting audiences and bringing people together with substance and with integrity. JALC has created a dynamic platform where our key constituents – jazz artists (beginner to grizzled veteran), fans (casual listeners to advanced scholars), educators (local band leaders to leading artist\-educators) and advocates (local community advocates to important national promoters) – can meet, engage, learn, and work towards common objectives.
About the Role
The Email Marketing Specialist supports the execution of email communications across the organization. This role focuses on building and sending email campaigns, maintaining audience lists, coordinating content and approvals, and supporting automated email communications that help drive audience engagement, ticket sales, subscriptions, memberships, and donations.
Working closely with the Marketing, Development, and Education teams, the Email Marketing Specialist translates campaign plans into clear, well\-formatted emails, maintains accurate audience segmentation, and helps ensure communications are delivered effectively and on schedule.
This role is highly detail\-oriented and operational, requiring strong organization, collaboration, and technical comfort with email marketing platforms and CRM systems.
Responsibilities
Email Content Development \& Deployment
- Build and deploy email campaigns across performance marketing, education, fundraising, and institutional messaging.
- Draft and format email content, edit copy, and build layouts that align with Jazz at Lincoln Center’s brand and voice.
- Coordinate with internal stakeholders to gather copy, images, and approvals needed for scheduled email sends.
- Prepare and schedule campaigns according to the marketing communications calendar.
- Ensure emails are formatted correctly across devices and email clients and meet internal quality standards for grammar, clarity, and presentation.
- Apply established email marketing practices to support deliverability, responsiveness, andaccuraterendering across major email clients.
CRM \& List Management
- Maintain day\-to\-day operations within the email marketing platform, including audience lists, data accuracy, and list hygiene.
- Build andmaintainaudience segments based on patron type (ticket buyers, subscribers, donors, educators, etc.) and engagement interests.
- Pull lists and prepare targeting selections for scheduled email campaigns.
- Work with Tessitura and Technology teams to helpmaintainclean and reliable data connections between systems.
- Support ongoing maintenance of audience data used for marketing communications.
Automated Email Communications
- Build andmaintainautomated email journeys such as welcome series, renewal reminders, abandoned cart reminders, and re\-engagement campaigns.
- Implement updates or adjustments to automated campaigns based on direction from marketing leadership.
- Support routine testing of subject lines, layouts, calls\-to\-action, and send timing to improve campaign performance.
- Follow internal guidelines and applicable data privacy requirements for email marketing communications.
Reporting \& Analysis
- Track email campaign performance metrics including open rates, click\-through rates, conversions, and unsubscribe activity.
- Prepare reports summarizing campaign results for internal teams.
- Support the creation and maintenance of dashboards that help teams understand audience engagement and campaign performance.
- Share observations from campaign results to help inform future communications.
Key Competencies
- Strong writing and editing skills with the ability to produce clear, engaging marketing communications.
- Attention to detail and commitment tomaintainingbrand voice and communication standards.
- Comfort working within email marketing platforms and CRM systems.
- Understanding ofaudience segmentation and email list management practices.
- Ability tomonitorcampaign metrics and summarize results.
- Strong organizational skills with the ability to manage multiple campaigns and deadlines simultaneously.
- Ability to coordinate across teams and navigate approval processes.
- Experience building andmaintainingautomated email communications.
- Familiarity with email deliverability considerations, accessibility standards, and responsive design.
- Working knowledge of email marketing compliance requirements such as CAN\-SPAM and related privacy practices.
- Collaborative approach and strong interpersonal communication skills.
Qualifications
- 4–6 years of experience supporting email marketing, digital marketing, or CRM\-driven communications.
- Hands\-on experience with email marketing platforms (such asWordfly, Salesforce Marketing Cloud, Mailchimp, or similar).
- Experience working with CRM systems; familiarity with Tessitura andWordflyor Salesforce Marketing Cloud preferred.
- Experience building segmented email campaigns and supporting automated marketing communications.
- Ability to interpret campaign performance data and summarize key results.
- Experience working in aperforming arts, nonprofit, cultural, or mission\-driven organization preferred.
Benefits
We offer a comprehensive benefits package including: generous PTO; medical, dental \& vision; a defined contribution plan and deferred compensation plans.
Work Location Expectations
At Jazz at Lincoln Center, we believe the best work happens in person, through collaboration, spontaneous conversation, and the kind of connection that reflects the spirit of jazz itself. While we do not offer formal hybrid arrangements, we approach real life with understanding: when things come up, we are flexible. That said, staff are expected to be on site whenever their role or schedule requires it, whether that is standard hours, evenings, or weekends, so that we can do our best work together.
Equal Opportunity Employer
Jazz at Lincoln Center is an equal opportunity employer that affords equal opportunities to all applicants, employees, contractors, and other covered persons, and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Jazz at Lincoln Center is committed to creating an inclusive, open, and respectful culture that reflects and embraces diversity.
Salary Context
This $74K-$83K 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 Jazz At Lincoln Center, 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 ($79K) sits 53% below the category median. Disclosed range: $74K to $83K.
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.
Jazz At Lincoln Center AI Hiring
Jazz At Lincoln Center has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $83K - $83K.
Location Context
AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% above the national 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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