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About This Role
Description:
Full\-time, Exempt
Background
Internationally recognized as a premier museum and research center, the Frick is known for its distinguished Old Master paintings and outstanding examples of European sculpture and decorative arts.
The collection originated with Henry Clay Frick (1849–1919\), who bequeathed his home, paintings, sculptures, and decorative arts to the public for their enjoyment. The institution’s holdings—which encompass masterworks from the Renaissance through the nineteenth century—have grown over the decades, more than doubling in size since the opening of the museum in 1935\. A critical component of the institution is the Frick Art Research Library, founded in 1920 by Helen Clay Frick, daughter of the museum’s founder. Recognized as one of the world’s top art history research centers, it has served students, scholars, and members of the public free of charge for generations.
The Frick has undergone a comprehensive renovation and was open in a temporary home, Frick Madison, from 2020 through early 2024, while renovations were underway at the mansion on 70th Street. In addition to special exhibition galleries and education spaces, we have added enhanced visitor amenities and accessible spaces. The Museum and Art Research Library reopened to the public in April 2025\.
Workplace Culture
At the Frick Collection, we pride ourselves on promoting an open and welcoming workplace culture that supports work\-life balance. The Frick strives to provide our employees with competitive salaries and exceptional benefits in a beautiful and pleasant work setting, while offering an excellent opportunity to appreciate some of the world’s finest works of art.
The Frick Collection provides equal opportunity to all employees and applicants for employment without regard to personal characteristics such as race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, or other characteristics protected by law. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
Position Summary
Reporting to the Associate Director of Retail and Product Development, the Retail Operations Manager will be responsible for the overall daily operation and work flow of the Retail department. Manager will also assist with E\-Commerce, inventory management, team management, and Shop merchandising.
Primary responsibilities:
- Ensures daily operations run smoothly and efficiently and our standards of excellence in customer service are upheld.
- Direct reports are the Associate Managers and Inventory Manager.
- Works in close partnership with Associate Director to effectively manage inventory and schedule product launches, customer events.
- Assists with merchandising of product in the Shop.
- Plays a major role in updating the E commerce workflow and growth of our online business.
- Submits all departmental invoices, credit card receipts, schedules monthly trainings.
- Supplies: monitors budget, handles ordering of general and custom supplies
- In collaboration with the management team, organizes staff events and team building exercises.
- Serves as department liaison with Marketing, Special Events, and Graphic Design departments.
- Leads physical inventory at the end of fiscal year.
Skills/Experience/Education
*We recognize that people come with a wealth of experience and talent beyond just the technical requirements of a job. If your experience is close to what you see listed here, please still consider applying.?*
- 5\+ years in Retail in a supervisory role, luxury retail experience a plus
- Knowledge of Big Commerce, Clover, and Counterpoint systems a plus
- Extremely detail oriented
- Excels at trouble shooting
- Excellent communication and writing skills
- Experience in a not\-for\-profit setting or cultural institution.
- Strong leadership skills including willingness and ability to enthusiastically support, engage, and work alongside all retail staff in executing daily operation and working directly with the public.
Requirements:
Physical Requirements
*The physical requirements of this role are needed to perform the essential job functions with or without reasonable accommodation(s).*
Physical requirements are comparable to most office roles. Ability to interact in\-perison with colleagues. Use common office tools and machines (computer, phone). Ability to traverse throughout the office and building(s) both inside and outside of the museum and visit different levels of the building. Ability to carry/transport materials weighing up to 20 or more pounds.
Benefits in Employment with the Frick Collection
Paid Holidays: Full\-time employees are eligible for 14 paid holidays, all federal holidays including Juneteenth, and Election Day and four floating holidays: two may be used in the first half of the calendar year, two may be used in the second half of the calendar year.
Sick and Vacation time: Eligible full\-time employees accrue up to 12 sick and 15 vacation days their first year of employment. In subsequent years, eligible full\-time employees accrue up to 12 sick days and 25 vacation days/year.
Paid Family leave: In addition to adhering to all federal family leave laws, we provide all eligible employees with paid bereavement and family leave.
Health, Dental and Vision insurance: all full\-time employees and their eligible dependents may enroll in employer sponsored benefits plans. Employees contribute to the cost of health insurance based on income level and type of coverage selected.
Short and Long Term Disability and Life Insurance: the Frick covers the entire cost of these benefits for all full\-time employees.
The life insurance benefit is up to three times the employee’s annual salary.
Retirement: The Frick supports all employees in planning for retirement by offering participation in a Tax Deferred Savings Plan – 403(b) and a defined benefit pension plan. We also offer retiree health benefits for retirees and their eligible dependents.
Wellness Programs at the Frick include an Employee Assistance Plan, a discount on Citi Bike memberships and a discount on bike helmets.
Additional benefits include discounted transit benefit, flexible spending accounts for health, dependent care and commuting costs.
Employment Status and Compensation
This role is a full\-time in person exempt role.
The annual salary for this role is commensurate with skills and experience with a salary range of $80,000\-$90,000\.
The Frick’s Museum Shop is open six days/week: Wednesdays through Mondays. Additionally, the Collection hosts events and other activities that require the museum shop to be open in the evenings. The Retail Operations Manager will be relied upon to work to support operations during regular opening hours and to support evening events as needed.
Application Process
Apply here or send resume and cover letter to:
Associate Director of Retail and Product Development
The Frick Collection
1 East 70th Street
New York, NY 10021
*Qualified candidates of diverse backgrounds are encouraged to apply for vacant positions at all levels.*
*This description shall not be construed as a contract of any sort for a specific period of employment.*
*Benefits subject to change and may differ based on employee status.*
Salary Context
This $80K-$90K 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 The Frick Collection, 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 ($85K) sits 49% below the category median. Disclosed range: $80K to $90K.
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 Frick Collection AI Hiring
The Frick Collection has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $80K - $90K.
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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