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About This Role
Description:
*Be a part of the best team in Property Management!*
Vesta Management, TX, is seeking to hire an affordable housing experienced, highly skilled, results driven Maintenance Technician to support maintenance operations at *Marshall Meadows Apartment Homes* in *San Antonio, TX*. We're looking for a hands\-on team player who takes pride in their work, is motivated to meet deadlines, and genuinely cares about creating a positive experience for our residents. *Join our team and be a part of Vesta’s success story!*
What we Offer:
At Vesta, we take pride in hiring the best talent in Property Management. We work hard and we have fun doing so. In addition to our generous benefits package, we offer service awards, performance bonuses, team member appreciation events and opportunities for growth. Our benefits include:
- Medical, dental \& vision insurance
- Company matched 401(K).
- Paid time off\- Vacation, sick, floating holidays
- 12 additional paid holidays
- Tuition Reimbursement
- PetPlan Pet Insurance
- Employee Assistance Program
- Long \& Short\-Term Disability Insurance
- AND MORE
The Maintenance Technician is responsible for performing all assigned maintenance tasks to ensure that the property meets safety, appearance, and operational standards. Quick response to resident service requests, taking appropriate action to resolve work orders. Responsible for efficient and fast turnaround of apartment make readies. This includes completing a make ready punch list and ensuring that vacant units are move in ready per expectations. Emergency on\-call, nights, and weekends required. May be required to drive a company vehicle. May also assist in maintaining the physical appearance, condition, cleanliness and curb appeal of the property.
Essential Functions:
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Assist with and attend resident retention initiatives (i.e., resident functions, promotions, monthly newsletters, etc.) and property\-issued communications/notices (i.e., bad weather, emergency, etc.)
- Preserves and respects resident, applicant, employee and company confidentiality.
- Report for on\-call duties to provide 24 hour/7day per week emergency maintenance service.
- Must be knowledgeable of inventory levels of parts and supplies and inform supervisor of shortages, while also ensuring that maintenance shop and current supplies are kept accessible and organized.
Ongoing Work Orders/Projects and Preventive Maintenance:
- Consistently maintain the overall attractiveness of the property, taking initiative as needed to keep the property looking professional and appealing to current and potential residents, owners, investors, and lenders.
- Regularly conduct inspections of and ensure that apartments, building systems, common areas, and grounds meet Vesta quality standards and expectations, by correcting any deficiencies.
- Report any maintenance or physical property needs to the Property Manager and/or lead maintenance personnel for work order input.
- Responsible for handling, completing, and documenting all assigned service requests/work orders, ensuring that our residents’ maintenance needs are met properly, quickly, thoroughly, and professionally. Maintenance and repair may include plumbing, HVAC, carpentry, appliances, carpeting, drywall, worn or defective parts, grounds, and electrical systems. May be responsible for pool maintenance, depending on property needs.
- Assists with moving appliances, abandoned furniture and unloading and storing supplies.
- Ensure unsafe conditions are corrected immediately, and practice “safety first".
- Communicate and maintain accurate records regarding preventative maintenance, work orders/service requests (received and completed), apartment make\-ready status, and assigned work\-in progress.
Make Ready:
- Prepare apartment for occupancy within three to five days of vacancy, in order to maximize occupancy.
- Trash out and clean out of food, furniture, appliances and other debris within assigned vacant unit.
- Prep assigned unit for painting and flooring.
- Timely and thorough completion of assigned items on make ready punch list, including, but not limited to; cleaning, painting, flooring, caulking, wall prep, removal and cleaning/replacement of receptacle and switch plate covers and light fixture bulbs, and holes in walls.
- While completing make ready punch list, inspect and report any additional maintenance needs including repairs or replacements not initially noted. Complete any additional tasks that are within manageable skill set.
- After final maintenance, painting, and floor work, the Maintenance Technician may be responsible for the last “sparkle”/touch prior to final move in ready inspection.
- Ensure ready apartments are inspected daily, communicate and input any new maintenance needs, and inform leasing of ready unit status for prospect showings.
- Other duties as assigned by management.
Knowledge, Skills and Abilities:
- Excellent interpersonal skills; strong verbal communication skills.
- Able to work independently; self\-motivated, takes initiative.
- Able to work well under pressure/emergency/time sensitive situations.
- Able to multitask and prioritize efficiently.
- Accepts responsibility and accountability.
- Honest and trustworthy; displays integrity.
- Professional, in appearance and action
- Shows adaptability.
- Able to troubleshoot problems for creative solutions.
- Organized and detailed.
Interested? APPLY NOW!!!
Requirements:
Required Education and Experience:
- 2 or more years of related experience.
- Apartment community experience required.
- Working knowledge of and proven skilled ability to successfully repair and maintain drywall, lock change, and light electrical, carpentry, flooring, plumbing.
- HVAC strongly preferred.
Additional Eligibility Qualifications:
- Multilingual a plus.
- Excellent communication skills
- Strong customer service philosophy with a CAN\-DO attitude
- Ability to participate in the emergency on\-call rotation.
- Successful completion of a background check and drug screen required.
- Valid Driver's License and clean driving record required.
*Vesta is an Equal Opportunity/Affirmative Action Employer. Vesta has an ongoing commitment to a diverse workplace free of discrimination and harassment. Vesta recruits, hires, trains, and promotes individuals in all job titles without regard to any protected characteristic, including but not limited to race, color, creed, religion, ancestry, sexual orientation, genetic information, national origin, age, sex, physical or mental disability, being a disabled veteran, veteran of the Vietnam era, or other eligible veteran, or any other protected category under any state or Federal laws. At Vesta, we are committed to a fair and equitable workplace.*
Salary Context
This $52K-$54K 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 Vesta Corporation, 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 ($53K) sits 68% below the category median. Disclosed range: $52K to $54K.
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.
Vesta Corporation AI Hiring
Vesta Corporation has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span San Antonio, TX, US, Worcester, MA, US, Hartford, CT, US. Compensation range: $54K - $105K.
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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