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About This Role
Executive Assistant to Vice President for Student Affairs
Classification
Full\-Time, Non\-Exempt
Department/Division
Student Affairs
Reports To
Vice President for Student Affairs
About King’s
King's College is a Catholic institution of higher education animated and guided by the Congregation of Holy Cross. King's pursues excellence in teaching, learning, and scholarship through a rigorous core curriculum, major programs across the liberal arts and sciences, nationally accredited professional programs at the undergraduate and graduate levels, and personal attention to student formation in a nurturing community.
We offer competitive total rewards, tuition remission for employees, 403(b) plans, and generous paid\-time\-off and holidays. Our culture is driven by our commitment to our mission, our community and our friendly, knowledgeable faculty and staff.
EEO Statement
King’s College does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, parental status, military service, or other non\-merit factors. We celebrate diversity by fostering a welcoming and inclusive environment where each member of King’s College feels respected with a sense of belonging.
Job Function
Provides administrative/secretarial support for the Vice President for Student Affairs and Associate Vice President for Student Affairs/Dean of Students and Division of Student Affairs.
Essential Elements
1\. Creates and maintains an office environment that celebrates, challenges and supports students in a caring and supportive manner consistent with the missions of the Division of Student Affairs and the College, its Catholic identity, and the Congregation of Holy Cross.
2\. Answers and screens incoming calls and greets visitors in a friendly and courteous manner.
3\. Provides service to students, faculty, and staff, providing information and referring them to appropriate college offices.
4\. Maintains and schedules administrative staff calendars (Outlook, Bookings).
5\. Coordinates purchasing for the office. Contacts service providers for the office copier, fax, printer and computer service and repair.
6\. Performs clerical functions such as typing reports, memos, and correspondence, and proofreads documents—including brochures and reports—for content accuracy and formatting.
7\. Prepares information, formats tables and charts, and consolidates various reports (e.g., the Student Life Committee\-Board of Directors, President’s Cabinet/Senior Staff, Divisional Leadership, Divisional assessment reports, divisional communications) as directed by VP/AVP.
8\. Assists in the development, proofreading, and editing of the Student Handbook.
9\. Coordinates publications (Off\-Campus Parent and Student brochures, Alcohol and Drug brochure, Student Conduct Manual, and VAWA publication).
10\. Support strategic planning initiatives housed within Student Affairs, inputs data when needed and documents information for attendees.
11\. Provides assistance with event planning and organization by working with Conference \& Events or outside agencies if off campus.
12\. Enters data and prepares reports using the Guardian system for student conduct, Care Team, Title IX, and other functions.
13\. Coordinates student conduct appeal process for Vice President and Associate Vice President.
14\. Manages the scheduling and planning of Administrative and College Student Conduct Panel Hearings, as well as the scheduling of interviews for the College Student Conduct Panel.
15\. Works closely with administrative hearing officers to track and follow up on student conduct cases and sanctions process. Tracks fines and restitution and conducts appropriate follow\-up for unpaid accounts.
16\. Enters the Datatel/Ellucian System holds for overdue fines, changing residency codes for off\-campus students and commuters, updates off\-campus student contact information, and enters missing student contact information and parent/guardian information.
17\. Prepares correspondence and maintains records for Sexual Harassment/Title IX cases under the direction of the Title IX Coordinator.
18\. Reviews and updates College web pages for the office (Student Affairs, Dean of Students, Title IX, etc.)
19\. Collates data for statistical reports, including the office semester report, student conduct information, and other compliance reports, including preparing tables, graphs and PowerPoint.
20\. Maintains confidential student records and evaluates requests for student record disclosure following FERPA and College policy.
21\. Maintains class attendance records. Notifies faculty and other administrative offices when a student is absent for several days due to a family or personal emergency.
22\. Provides administrative support to other departments within the division as needed (i.e., project initiatives, assistance with data entry and support to a function without administrative secretarial support, or personnel transitions/coverage needs).
23\. Evaluates inquiries and situation and contacts appropriate staff when the Vice President or Associate Vice President is unavailable.
24\. Maintains divisional staff listserv and seeks approval from the VPSA and/or AVPSA on divisional communications prior to distribution.
Non\-Essential Elements
1\. Evaluates and maintains appropriate archival files for the division of student affairs in consultation with the VPSA.
2\. Performs other related duties as assigned.
Required Skills, Training, and Experience
1\. Excellent computer (i.e., Windows, Word, Excel, Outlook, PowerPoint, Canva and aptitude to learn software systems such as Ellucian Colleague, CROA/Entrinsik Informer, Guardian, One Hub, eRezLife) and typing skills.
2\. Excellent organizational ability and interpersonal skills.
3\. Desire to work closely with students, families, and the public.
4\. Ability to work independently.
5\. Ability to manage projects from organization to completion.
6\. Ability to work with individuals of diverse backgrounds.
Physical Conditions
Typical office working conditions.
Limited evening and weekend work is required.
Job Type: Full\-time
Pay: From $19\.00 per hour
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Paid time off
- Parental leave
- Retirement plan
- Tuition reimbursement
- Vision insurance
Work Location: In person
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 King's College, 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.
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.
King's College AI Hiring
King's College has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Wilkes-Barre, PA, US.
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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