Interested in this AI/ML Engineer role at Habitat for Humanity of Greater Palm Beach County?
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About This Role
*Not your average retail job.*..Store Hours: Monday through Friday 9am to 6pm | Saturday 9am to 4pm | Closed Sundays.
Position is for a Manager in Training that would work between the Greenacres ReStore (4639 Lake Worth Rd, Greenacres, FL) and the Delray Beach ReStore (1900 N Federal Hwy, Delray Beach, FL)
*Why work for Habitat GPBC? Read our story*: www.habitatgreaterpbc.org
POSITION TITLE: Manager in Training
PURPOSE: This position will be trained to be responsible for the daily management of ReStore operations and sales, representing Habitat for Humanity of Greater Palm Beach County, in a professional way true to our mission. The Manager in Training will work between the two southern ReStores to learn the role so they are ready to be promoted to a Co-Mgr. or General Manager when needed. There might be times that travel to the northern ReStores (Jupiter, FL & Riviera Beach, FL) for training would also be necessary.
KEY RESPONSIBILITIES: (Role would learn all of these responsibilities so they are ready to step into a management role when needed)
- Oversees and manages all ReStore operations including; sales, donations, planning, budgeting, scheduling, safety, merchandising, customer service and business plan execution in coordination with the Director of ReStores, and the VP of Retail.
- Provides direct supervision of all paid ReStore staff and volunteers.
- Keeps the Director of the ReStores current on all ReStore activities, plans, programs, events, sales and donation status.
- Develops and implements the ReStore’s annual budget in coordination with the Director of ReStores and the VP of Retail.
- Develops or assists in all ReStore marketing efforts with emphasis on “more for less” advertising and better community awareness.
- Develops, implements, and ensures strict adherence with an OSHA compliant safety program for the ReStore and store activities.
- Ensures that all ReStore operations and related retail activities comply with Affiliate policies and HFHI Covenant.
- Ensures that all Affiliate labor standards and cash handling procedures are adhered to by the ReStore.
- Works closely with all existing business partners (contractors, subcontractors, and vendors) and continuously solicits new business partners to ensure the best possible pricing and quality products and service.
- Engages in fundraising and solicits in-kind donations from business partners in coordination with the VP of Retail.
- Works to broaden contacts with local organizations to ensure a steady supply of new and high-quality donations to the ReStore.
- Monitors ReStore expenditures to control costs and increase net revenue.
- Monitors ReStore staffing levels to control payroll and employee benefits costs.
- Actively works with the Director of ReStores and the Volunteer Coordinator to secure more volunteers for the ReStore and implement “volunteer orientation” at store level to increase productivity. Train and assign duties to Volunteers,
- ReStore’s staff representative to the Retail Committee. Provides advice and executes ReStore action plans.
- Develops relationships with other area ReStore managers to identify “best practices” and programs that are mutually beneficial.
- Maintains ReStore organizational charts related to store needs and productivity.
- Responsible for evaluating the performance of the paid ReStore staff on a quarterly basis.
- Implements and faithfully executes all policies, plans, and procedures adopted by the Board of Directors and directions given by the Chief Executive Officer and the VP of Retail.
- Performs other duties as assigned.
Essential Job Functions:
- Ability to read and interpret reports, write reports and business correspondence
- Computer skills: Microsoft Office Suite programs and mobile devices.
- Ability to sit stationary or walk and stand for extended periods of time. Must be able to twist, turn, bend, stoop, climb, reach, push, pull and subject to environmental conditions, noise and hazards.
- Worker is required to have visual acuity to operate motor vehicles and/or heavy equipment and small equipment and computer devices.
- Typical retail store settings combined with outside environmental conditions; subject to noise, vibration, hazards and activities occurring inside and outside and often extreme temperatures.
- Medium work. Exerting up to 50 pounds of force occasionally, and/or up to 30 pounds of force frequently, and/or up to 10 pounds of force constantly to move objects.
- Travel throughout the county may be required, fast paced environment with medium-high stress based on multiple projects, deadlines, timelines and the need to react quickly and respond quickly.
Experience:
- Bachelor’s Degree preferred or equivalent retail experience and training.
- A minimum of three (3) years of supervisory or managerial experience in a retail environment.
- Proven customer service excellence in a retail store setting.
Preferred attributes:
- Strong commitment to the Habitat for Humanity mission, principles, and guidelines.
- Effective communication and listening skills.
- Attention to detail with strong problem-solving skills.
- Ability to work with and serve a diverse demographic.
- Strong aptitude to work in a team environment and to seek partnerships in planning and plan execution.
- Represent Habitat for Humanity in the best possible light at all times.
REQUIRED LICENSE OR CERTIFICATION:
- Valid Driver’s License
- Must meet Affiliate’s driver guidelines for insurability
- Required to pass a Background Check and Drug Screen prior to being hired.
- Random quarterly drug screens are also performed at Habitat for Humanity.
Habitat for Humanity of Greater Palm Beach County's Core Values:
· Elevate Others: Empower each other to grow, thrive and rise.
· Go the Extra Mile: Demonstrate dedication and commitment to supporting our mission.
· Honor Commitments: Ensure reliability and follow-through in all financial matters.
· Constructive Problem Solving: Focus on solutions and continuous improvement.
· Do the Right Thing: Uphold integrity and ethical standards in all actions.
Habitat for Humanity of Greater Palm Beach County is an equal opportunity employer and seeks to employ and assign the best qualified personnel for all our positions in a manner that does not unlawfully discriminate against any person because of race, color, religion, gender, marital status, age, national origin, physical or mental disability, sexual orientation, veteran/reserve national guard status, or any other status or characteristic protected by law.
Habitat for Humanity of Greater Palm Beach County Inc. is committed to safeguarding the health of our employees and providing a safe work environment for everyone. Because of this, the Company has implemented a Drug-Free Workplace Policy to comply with Florida Statute 440.102(Drug Free Workplace).
Job Type: Full-time
Pay: $43,000.00 - $47,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee discount
- Flexible spending account
- Health insurance
- Paid time off
- Parental leave
- Vision insurance
Experience:
- Retail management: 1 year (Preferred)
- employee development: 1 year (Preferred)
Language:
- Multilingual (Preferred)
License/Certification:
- Driver's License (Preferred)
Work Location: On the road
Salary Context
This $43K-$47K 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 Habitat for Humanity of Greater Palm Beach County, 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 $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 ($45K) sits 71% below the category median. Disclosed range: $43K to $47K.
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.
Habitat for Humanity of Greater Palm Beach County AI Hiring
Habitat for Humanity of Greater Palm Beach County has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Boynton Beach, FL, US, Palm Beach Gardens, FL, US. Compensation range: $47K - $47K.
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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