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About This Role
*Current Employees and Students: If you are currently employed or enrolled as a student at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process.*
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Position Title:
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Workforce Training Advisor (Business Development Specialist)
Job Category:
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Academic Staff
Employment Type:
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Regular
Job Profile:
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Outreach Specialist
Job Duties:
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The Workforce Training Advisor (Business Development Specialist) advances the University of Wisconsin\-Green Bay’s mission by building strong workforce training partnerships through direct outreach, cold calls, and relationship development that support regional growth and expand access to education throughout Northeast Wisconsin. As the primary outbound business development lead, this role focuses on prospecting, cold outreach, and securing new customized training and certificate engagement with small and mid\-sized employers acros s the University’s 16\-county region—primarily in manufacturing, professional services, and financial services. Guided by a defined sales process, the Advisor drives measurable revenue growth while advancing fearlessly to meet evolving workforce needs.
Aligned with UW–Green Bay’s strategic priorities and core values, the Advisor empowers success by connecting employers with solutions that strengthen talent and community impact. While program design and delivery transition to internal partners, the Advisor remains a trusted relationship builder—fostering repeat engagement and collaboration. This mission\-driven role reflects UW–Green Bay’s brand promise to provision access, build community, and move forward together. Together, We Rise.
Key Job Responsibilities:
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- Develops and evaluates curriculum and programs and provides recommendations for improvement
- May assist with the monitoring of outreach program budget spending
- Leads the implementation of programs, policies, and procedures through oversight of day\-to\-day activities for program staff and student and community volunteers
- Schedules and secures resources and communicates logistics in support of an outreach program, including business development and new account acquisition
- Identifies, promotes, and maintains external partnerships to support the outreach program, including account cultivation and relationship management
- Delivers outreach program content and materials to community members
- Researches, develops, and facilitates outreach program content and materials
Department:
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Continuing Education
Compensation:
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Compensation range of $56,522 to $65,000\. This position is exempt from the overtime provisions of the Fair Labor Standards Act (FLSA).
Required Qualifications:
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- Associate's degree in Business, Communications, or related field
- Excellent written and verbal communication skills, including professional email, phone, and presentation abilities
- Valid Wisconsin driver’s license and ability to travel throughout the 16\-county service region
Preferred Qualifications:
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- Bachelor's Degree in Business, Communications, or related field
- 2\-4 years of B2B sales, business development, or account management experience with documented success meeting activity and revenue targets
- Demonstrated ability to hunt for new business; weekly cadence of online engagement, prospecting emails and making cold calls, to generate new business opportunities
- Experience using CRM systems (Salesforce preferred) to manage pipeline and track sales activities
- Proficiency with LinkedIn for professional networking and prospecting
- Strong consultative selling skills with the ability to identify business needs through discovery conversations
- Familiarity with workforce development, corporate training, or higher education environment
- Experience building relationships with executives and senior decision makers
Conditions of Appointment:
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Some travel is required for necessary meetings, workshops, conferences, etc. Occasional evening and/or weekend work is expected and will be assigned by supervisor as needed.
This position may have the option to work on\-campus or a hybrid schedule, subject to approved telecommuting request. The home campus of this position is Green Bay.
Position is a full\-time Academic Staff appointment. A pre\-employment education check which includes, but is not limited to, the verification of academic credentials will be conducted on the finalist(s). A criminal conviction investigation will be conducted on the finalist(s) and if there is prior work history within the last 7 years with Universities of Wisconsin, a personnel file review check for employee misconduct. In compliance with the Wisconsin Fair Employment Act, the University does not discriminate on the basis of arrest or conviction record.
The University of Wisconsin\-Green Bay does not offer H\-1B or other work authorization visa sponsorship for this position. Candidates must be legally authorized to work in the United States at the time of hire and maintain work authorization throughout the employment term. If you have questions regarding this, please contact Human Resources.
How to Apply:
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Click the Apply button and follow the prompts on the screen.
Please be sure to complete all required fields, and include all required documents before submitting your application. Once submitted, you will not be able to edit or attach any application materials. Files must be complete to be considered. Please include the following documents:
- Cover letter specifically addressing qualifications for the essential job functions
- Resume
Application Deadline:
To ensure consideration, please submit application materials by Sunday, April 5, 2026 .
Contact Information:
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If you have any questions, need accommodations, or submitted your application with missing materials, call or email:
Human Resources
Phone: (920\) 465\-2390
Email: jobs@uwgb.edu
The Successful Candidate
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The successful candidate will be expected to work inclusively and respectfully within a diverse campus community and practice civility in the workplace. The University welcomes applicants who are dedicated to the appreciation and promotion of inclusivity and equity as crucial components in the pursuit of organizational excellence.
In addition, the successful candidate will have strong oral, written, interpersonal, and organizational skills, demonstrated integrity and strong leadership, and the willingness to work independently and as part of a collaborative team. The University invites applicants who are dedicated to enriching the quality of life for students and the community by embracing the educational value of diversity, promoting environmental sustainability, encouraging engaged citizenship, and serving as an intellectual, cultural, and economic resource.
Benefit Details
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The Universities of Wisconsin provides an excellent benefits package to meet the diverse needs of its employees. For benefits eligible positions, this includes several health insurance options, with annual deductibles as low as $250/individual and $500/family. Our benefits package also includes dental, vision, several life insurance options, AD\&D and Accident insurance and Flexible Spending and Health Savings Accounts. We participate in the Wisconsin Retirement System (WRS), where employer contributions begin immediately, and employees are fully vested after 5 years of service. The Universities of Wisconsin also provides supplemental retirement savings programs including a 403(b) and Deferred Compensation.
In addition, eligible employees receive several types of paid leave benefits, which are prorated for employees working less than 100%. This includes 9 legal holidays, 36 hours of personal holiday and between 96\-130 hours of sick leave annually and paid parental leave. Eligible employees earn 13\-27 days of vacation each year, depending on years of service and employment type.
For more details, please review the benefit quick guide linked below.
- UW System Employee Benefits Brochure
- Total Compensation Estimator
Employee Misconduct
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All final candidates will be asked to provide names, email contact information, and/or phone numbers for three (3\) references, with at least one being from a manager or supervisor, during the interview process. All final candidates must be asked, prior to hire, whether they have been found to have engaged in, are currently under investigation for, or left employment during an active investigation in which they were accused of employee misconduct, sexual violence or sexual harassment. When obtaining employment reference checks, these same misconduct, sexual violence or sexual harassment questions must also be asked.
Confidentiality Statement
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The University of Wisconsin System will not reveal the identities of applicants who request confidentiality in writing, except that the identity of the successful candidate will be released. See Wis.Stat. sec. 19\.36(7\) .
Annual Security Report
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For more information regarding the University of Wisconsin\-Green Bay and the surrounding area, see our Campus and Community section. For Campus Safety information see our University Police website and our Annual Security Report (for a paper copy please contact the Office of Human Resources at (920\) 465\-2390\). This report includes statistics about reported crimes, as well as information about crime prevention and campus security policies and procedures.
UW is an Equal Opportunity Employer
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Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, disability, status as a protected veteran, or any other bases protected by applicable federal or State law and UW System policies. We are committed to building a workforce that represents a variety of backgrounds, perspectives, and skills, and encourage all qualified individuals to apply.
Salary Context
This $56K-$65K 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 University of Wisconsin-Green Bay, 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 ($60K) sits 64% below the category median. Disclosed range: $56K to $65K.
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.
University of Wisconsin-Green Bay AI Hiring
University of Wisconsin-Green Bay has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Green Bay, WI, US. Compensation range: $65K - $65K.
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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