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About This Role
Position Details
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Position Information
About Hofstra
Hofstra University is nationally ranked and recognized as Long Island’s largest private university located in Hempstead, N.Y. When you work at Hofstra, you join a team of talented professionals committed to preparing students for the challenges of tomorrow, in an environment that cultivates learning through the free and open exchange of ideas for the betterment of humankind. The work we do at Hofstra supports the education and well\-being of our students, and the workforce of the future. While working towards this mission, employees can take advantage of many enriching experiences on campus. Whether it’s a lunchtime lecture, a Division I NCAA athletics game, a musical concert, a theatre performance, or a visit to one of our two accredited museums, there is always something exciting to do at Hofstra. Enjoy the ease of going to the fitness center, taking a swim, or grabbing a bite to eat without having to leave our beautiful campus! Hofstra University is dedicated to recruiting and retaining a highly qualified and diverse academic community of students, faculty, staff, and administrators respectful of the contributions and dignity of each of its members. We welcome applications from individuals of all backgrounds and experiences and are committed to building a diverse and inclusive community.
Position Title Mailroom Clerk, Grade B
Position Number 899502
Position Category Staff
School/Division Facilities and Operations
Department Print and Mail Services
Full\-Time or Part\-Time Full\-Time
Description
Reporting to the Director of Print and Mail Services, the Senior Clerk handles many clerical services and responsibilities relating to the daily operations of Print and Mail Services.
Responsibilities include, but are not limited to:* Sorts and organizes both U.S.P.S. and on\-campus mail to ensure timely daily deliveries.
- Delivers mail and packages along designated campus routes for faculty and administrators.
- Operates University vehicles, including vans and carts, in a safe and efficient manner.
- Supports on\-campus delivery operations twice daily, including the distribution of mail and packages.
- Processes metered mail and packages across all mail classes in accordance with postal regulations.
- Operates Quadient mail machines and related software programs (or comparable systems) with accuracy and care.
- Provides exceptional customer service through phone, email, in\-person interactions, work tickets, and service desks, ensuring clarity and professionalism in all communications.
- Assists in the preparation and handling of bulk mailings as needed.
- Prepares and meters all types of outgoing mail in coordination with departmental procedures.
- Understands, operates, and troubleshoots industry\-standard Mail Services technologies and learns to use print production equipment such as large\-format printers, cutters, folders, laminators, shrink wrappers, binders, and inserters.
- Prepares, prints, and mounts posters and visual materials as needed, and utilizes WebCRD or comparable print management software.
- Can be trained on how to operate forklifts and other material\-handling equipment as needed.
- May perform other duties not specifically identified above but which require the same degree of skill normally included within the above job title.
Hours: Monday through Friday from 9am to 5pm.
Subject to bumping
Qualifications
- A valid New York state driver’s license is required to operate a golf cart and mail van.
- Proficiency in Microsoft Word and Excel.
- Ability to work independently.
- Flexible availability to work holidays and overtime, when necessary.
- Working knowledge of Quadient (or similar) mail machines, EMS or comparable mail management software.
Preferred Qualifications
- Knowledge of print and mail center functions and USPS regulations preferred.
- Knowledge of WebCRD is a plus.
Special Instructions
Deadline Open Until Filled
Date Posted 01/22/2026
EEO Statement
Hofstra University is an equal opportunity employer and is committed to extending equal opportunity in employment to all qualified individuals without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, national or ethnic origin, physical or mental disability, marital or veteran status or any other characteristic protected by law.
Salary/Salary Range $34,955
Additional Information
*Hofstra University provides the above salary\* as a good faith estimate of the starting pay range which considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and education. In addition to the salary offered, we offer a collegial and inclusive culture, and a benefits program which includes generous paid time off, paid holidays, tuition remission for employees and eligible dependents, and a retirement plan with University contributions.*
- *Salary ranges indicated for positions covered under a Collective Bargaining Agreement are in accordance with the CBA.*
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 Hofstra University, 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.
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.
Hofstra University AI Hiring
Hofstra University has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Hempstead, NY, US. Compensation range: $525K - $525K.
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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