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Retail Assistant Manager
Non-Exempt/Hourly
Full-Time 40 Hrs. Avg. Per Week
Benefits Eligible
Mission Statement:
Goodwill Industries of Mississippi, Inc.’s mission is to transform lives through lifelong learning and meaningful work. The expectation of this position is to achieve organizational, team and personal goals in alignment with our mission and services offered.
Position Summary:
- The Retail Assistant Manager is responsible for overseeing the daily operations of the retail Location as directed by the Retail Store Manager. Works closely with the Retail Sales Executive to coordinate and determine the most cost-effective backroom processes, and to gather the best sales team possible. Serves as a positive role model by providing training and developing the skills of employees and clients. Addresses customer needs by immediately resolving conflict and inspiring long-term customer relationships.
Primary Duties:
- Achieve sales quota for store by maximizing production and sales from store operations.
- In the absence of the Retail Store Manager, knowledgeable and able to manage all store activities in a professional manner to ensure maximum customer satisfaction and to provide security and protection of donated merchandise.
- Supervise production functions such as: receiving donations, issuing receipts, sorting, and selecting merchandise, pricing and marking items; performing these and other production functions personally, as determined by the VP Donated Goods Retail.
- Attend all loss prevention/safety meetings and promotes a safe environment for employees, clients, and customers. Responsible for learning the material, training subordinates, enforcing all policy, procedures, and audit requirements relative to the meetings.
- Ensure merchandise is placed on sales floor effectively and that customer service is provided. Maintain a pleasant and polite customer service experience.
- Ensure banking procedures are performed accurately.
- Handle cash register functions and transactions including sales, voids, correct pricing, and giving receipts to customers. Ensure all cashiers are promoting the Roundup Program by asking each customer that comes through checkout if they would like to donate.
- Assist in performing all necessary personnel functions as determined by company policies and procedures including record keeping, scheduling, payroll management, monthly budget, disciplinary functions, evaluations, and training.
- Responsible for performing and supervising housekeeping duties. These duties include but are not limited to cleaning and straightening of the sales floor and production areas by sweeping, mopping, washing and/or dusting as needed.
- Perform necessary record keeping and reporting of money, sales, and production in an accurate and timely manner. This includes, but not limited to, the correct operation and utilization of the Point-of-Sale (POS) equipment. All issues, problems or concerns with the POS system are reported immediately to the Retail Sales Executive.
- Enforce and effectively communicate company policies and procedures to all employees.
- Maintain a high level of confidentiality.
- Perform all other duties as assigned.
Required Values:
- Personal accountability with a high degree of integrity and honesty, while understanding and observing the importance of confidentiality.
- Promotes dignity, diversity, excellence, and opportunity in meaningful work.
- Strong sense of grateful service and urgency.
Requirement(s):
- High School Diploma/GED preferred or at least one year of management experience in food services, manufacturing, production, or retail in lieu of education.
Certification(s):
- National Retail Federation (NRF) Certification within one year of job acceptance.
Knowledge, Skills and Abilities:
- Basic judgment skills to determine merchandise/donation value.
- Ability to communicate effectively both orally and in writing.
- Advanced math skills, including basic accounting and cash control procedures.
Additional Requirements:
- Supports the mission and vision of Goodwill Industries of Mississippi, Inc.
- Open availability.
- Ability to transfer to other working locations, as directed by management.
- Maintains a valid driver license with an acceptable Motor Vehicle Record
- Working knowledge of computers, including the Microsoft Office Suite.
- Promotes and demonstrates ethical practices in all activities.
- Promotes a safe work environment and follows all CARF requirements.
- Ability to pass alcohol/drug screenings, criminal background check and any insurance driving record check.
Physical Requirements:
- Works in an environment with occasional high stress, with potentially short deadlines.
- Stands and walks for most of the workday occasionally sits.
- Routinely bends, stoops, pulls, pushes, reaches, kneels, twists, turns throughout the day.
- Ability to lift up to 25 pounds in retail environment; 50 pounds in Donations/ADC/ Aftermarket environment, or the ability to do so safely.
Travel:
Minimal travel required. May travel to other locations to assist with management duties or training. Some travel for meetings, conferences or training may be required.
The above statements are intended to describe the general nature and level of the work being performed by an individual assigned to this work. This is not an exhaustive list of all duties and responsibilities. Goodwill Industries of Mississippi, Inc.'s management reserves the right to amend and change responsibilities to meet business and organizational needs as necessary.
Salary Context
This $27K-$29K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At GOODWILL INDUSTRIES OF MISSISSIPPI, 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 in Demand for This Role
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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($28K) sits 82% below the category median. Disclosed range: $27K to $29K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
GOODWILL INDUSTRIES OF MISSISSIPPI AI Hiring
GOODWILL INDUSTRIES OF MISSISSIPPI has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Ridgeland, MS, US. Compensation range: $29K - $29K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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