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About This Role
### Description
OPEN DATE: March 31, 2026
CLOSING DATE: April 24, 2026
POSITION TYPE: Trust Fund
APPOINTMENT TYPE: Permanent
SCHEDULE: Full Time
DUTY LOCATION: Washington, DC
Position sensitivity and risk:
Low Risk Non\-Sensitive
Open to all qualified applicants
What are Trust Fund Positions?
Trust Fund positions are unique to the Smithsonian. They are paid for from a variety of sources, including the Smithsonian endowment, revenue from our business activities, donations, grants and contracts. Trust employees are not part of the civil service, nor does trust fund employment lead to Federal status. The salary ranges for trust positions are generally the same as for federal positions and in many cases trust and federal employees work side by side. Trust employees have their own benefit program, which may include Health, Dental \& Vision Insurance, Life Insurance, Transit/Commuter Benefits, Accidental Death and Dismemberment Insurance, Annual and Sick Leave, Family Friendly Leave, 403b Retirement Plan, Discounts for Smithsonian Memberships, Museum Stores and Restaurants, Credit Union, Smithsonian Early Enrichment Center (Child Care), Flexible Spending Account (Health \& Dependent Care).Conditions of Employment* Pass Pre\-employment Background Check and Subsequent Background Investigation for position designated.
- Complete a Probationary Period.
- Maintain a Bank Account for Direct Deposit/Electronic Transfer.
- The position is open to all candidates eligible to work in the United States. Proof of eligibility to work in U.S. is not required to apply.
- Applicants must meet all qualification and eligibility requirements within 30 days of the closing date of this announcement.
### OVERVIEW
Come join a team of dedicated staff at an exceptional time in the Smithsonian’s history during the Smithsonian Campaign for Our Shared Future. The Smithsonian has surpassed its $2\.5 billion fundraising goal one full year ahead of schedule, a milestone that comes as the nation prepares to commemorate its 250th anniversary in 2026\. This achievement marks the largest fundraising effort in the history of any cultural organization and represents a defining moment for the Institution and the country it serves.
The Our Shared Future campaign has advanced the Smithsonian’s reach and impact, empowering the institution to find solutions to today’s most pressing challenges. The Smithsonian has built a model fundraising organization, driven by talented staff across our many museums, research centers and cultural centers. This position offers exciting opportunities for the successful candidate to make a significant impact on the future of the Smithsonian. There is no better time to join this amazing Institution.
The Office of Advancement oversees and guides the fundraising efforts of the entire Smithsonian and is home to the central advancement organization for the Institution. In addition to raising significant support for a variety of Smithsonian initiatives, the Office of Advancement provides support services to advancement offices across the Institution. The office engages with staff throughout the Smithsonian in accomplishing their goals.### DUTIES AND RESPONSIBILITIES
The Assistant Director, Online Engagement and Fundraising serve as the strategic leader for digital acquisition, renewal, sustainer, and unit‑based digital fundraising growth across an evolving enterprise technology environment.
This position is reported to the Director, Strategy and Member Experience and is part of the Office of Advancement. This role owns the vision and execution of digital fundraising strategy, leveraging Salesforce, Marketing Cloud, Data Cloud, and associated platforms to scale revenue, strengthen member engagement, support unit needs, and create an integrated omni‑channel experience. A key responsibility is the Assessment, development and operationalization of a plan to support unit‑based digital fundraising strategy and email execution as part of the Membership COOP shared services offerings.
Key responsibilities includes the following:* Develop and implement a multi\-year strategic vision to grow digital fundraising for membership, sustainers, and donor upgrade pathways.
- Lead digital acquisition, renewal, reinstatement, lapsed recovery, upgrade, auto renewal, and sustainer/monthly giving strategies.
- Oversee and execute campaigns across: Salesforce CRM, Marketing Cloud (including Journey Builder, Automation Studio, Email Studio), Data Cloud / CDP, Validity Email Success Platform, Involve.me, FundraiseUp, and Ticketure.
- Manage a team of 4–6 marketers, coordinators, or digital specialists.
- Oversee end to end project management using tools such as Asana, ensuring transparency, timeliness, and strong cross team coordination.
- Serve as the primary point of contact for external strategic partners, consultants, and agency.
### QUALIFICATION REQUIREMENTS
The minimum qualifications for this position are:* 8\+ years of experience in digital marketing, digital fundraising, membership programs, or direct response marketing.
- Deep knowledge of Salesforce CRM, Marketing Cloud, and ideally Data Cloud/CDP, including multi‑unit data management and segmented communication workflows.
- Experience with digital fundraising tools, including email deliverability platforms, form builders, donation platforms, ticketing systems, and CRM integrations, particularly in decentralized or multi‑unit environments.
- Demonstrated ability to manage and grow monthly giving/sustainer programs at scale across varied audience segments.
- Strong understanding of omni‑channel marketing, segmentation, analytics, donor lifecycle management, and how these strategies adapt across units with differing needs.
- Experience leading and developing teams in a fast‑paced, resource‑constrained, and cross‑unit environment.
- Excellent project management skills, including comfort with Asana or similar platforms, especially for coordinating multi‑unit workflows, templates, and SLAs.
- Proven ability to operate with high autonomy, navigate ambiguity, and solve complex technical and operational challenges across multiple stakeholder groups.
- Ability to adapt marketing and fundraising strategies to evolving privacy, data governance, and security requirements, including consent management, data minimization, and compliant segmentation practices across decentralized units.
- Proven ability to navigate ever‑changing data environments, shifting integrations, and platform constraints while ensuring continuity of digital fundraising operations and alignment across central and unit‑level stakeholders.
- Experience supporting or leading shared‑service models, including building scalable processes, frameworks, and governance for decentralized digital execution.
Applicants, who wish to qualify based on education completed outside the United States, must be deemed equivalent to higher education programs of U.S. Institutions by an organization that specializes in the interpretation of foreign educational credentials. This documentation is the responsibility of the applicant and should be included as part of your application package.
Any false statement in your application may result in your application being rejected and may also result in termination after employment begins.
Application Instructions
Interested candidates should submit their resumes and a cover letter by April 24, 2026\. Resumes should include a description of your paid and non\-paid work experience that is related to this job; starting and ending dates of job (month and year); and average number of hours worked per week. Relocation expenses are not paid.
What To Expect Next: Once the vacancy announcement closes, a review of your resume will be compared against the qualification and experience requirements related to this job. After review of applicant resumes is complete, qualified candidates will be referred to the hiring manager.
The Smithsonian Institution provides reasonable accommodation to applicants with disabilities where appropriate. Determinations on requests for reasonable accommodation will be made on a case\-by\-case basis. To learn more, please review the Smithsonian’s Accommodation Procedures.
The Smithsonian Institution is an Equal Opportunity Employer. To review the Smithsonian’s EEO program information, please click the following: https://www.si.edu/oeo.### About Smithsonian Institution
Founded in 1846, the Smithsonian is the world’s largest museum and research complex of 21 museums and galleries, the National Zoo and Conservation Biology Institute, and 14 education and research facilities. There are more than 6,500 Smithsonian employees, including approximately 500 scientists. The total number of objects, works of art and specimens at the Smithsonian is estimated at more than 157 million.
Salary Context
This $143K-$187K range is above 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 Smithsonian Institution, 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. Director-level AI roles across all categories have a median of $244,288. Disclosed range: $143K to $187K.
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.
Smithsonian Institution AI Hiring
Smithsonian Institution has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Washington, DC, US. Compensation range: $65K - $187K.
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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