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About This Role
Description:
*Be a part of the best team in Property Management!!*
Founded in 1981, Vesta Corporation has grown to one of the top affordable housing property management companies in the country. As we continue to grow, now is the perfect time to join our team! We are currently seeking a Regional Maintenance Manager to join our team in the Northeast Region *(Connecticut, Massachusetts \& Northern New England).*
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 Regional Maintenance Manager is responsible for oversight of all physical plant operations and maintenance work for multiple Vesta Communities, including staff training and evaluation, timely completion of work orders by assigned properties’ maintenance staff, timely completion of unit turns, deployment of regular and preventative maintenance programs, unit and grounds inspections, and technical assistance. The Regional Maintenance Manager is also responsible for special projects, including capital improvement projects, as well as creating and executing physical NSPIRE and other 3rd party preparation inspections.
Administrative Responsibilities
- Conduct regular site and unit inspections for adherence to company maintenance and safety standards; document courses of action, priorities and provide training or technical assistance based upon findings.
- Identify physical and staffing needs at properties and work with staff and management to address them.
- Prepare and maintain inventory of equipment, tools, and supplies at each property. Work with sites’ Property Managers to replenish, as necessary.
- Monitor completion of work orders received by maintenance staff and review with Area Maintenance Supervisor (AMS), Property Manager(s) (PM) or Regional Manager (RM) as necessary.
- Review prospective employee applications and assist with interviews as requested.
- Make recommendations for contract services and supervise contract workers when needed.
- Work with PM’s to create budgets related to supply needs.
- Work with maintenance staffs, and PMs to adhere to unit turns within budget and 5 \- 7 day make ready time frame.
- Ensure required maintenance reports are completed and submitted in a timely and accurate fashion.
- Work with RM and PM to create property capital improvement budgets.
- Review and prepare all maintenance service contracts with Assistant Director of Physical Plant.
- Maintain all site\-based facility licenses and certifications with local licensing authorities under direction of Assistant Director of Physical Plant.
- Review internal monthly reporting and logs for compliance and accuracy
Supervisory and Training Responsibilities:
- Evaluate timeliness of completion of work orders and provide feedback to RM and PM.
- Onboard and develop maintenance staff.
- Serve as a role model for maintenance staff.
- Ensure there is always on\-call coverage in the region.
- Identify potential maintenance leaders for promotion and provide feedback to RM and PM.
- Ensure that job descriptions are developed, that regular performance evaluations are prepared and delivered to maintenance staff working in collaboration with the Human Resources Department.
REAC/3rd Party Inspection Readiness:
- Ensure properties are prepared for 3rd party inspections, including but not limited to NSPIRE inspections.
- Prepare plans of action to cure identified deficiencies under the supervision of the Assistant Director of Physical Plant and Vice President of Operations.
- Prepare properties for noticed NSPIRE inspections and attend inspections.
Project Management:
- Create Scope of work
- Obtain and review competitive bids and contractor’s insurance documents
- Prepare General Service Contract for review by Director or Assistant Director of Physical Plant
- Schedule work with contractor taking property’s needs into account
- Oversee/Communicate with contractor as work is taking place
- Review final product and sign off on work
Competencies:
- Demonstrated skills and management experience of preventative and ongoing maintenance of a multifamily property.
- Experience in electrical, carpentry, HVAC, plumbing, and remodeling.
- Experience with electrical systems, appliances, circuits and fixtures.
- Experience with interior and exterior painting.
- Understanding of replacement flooring, glass and lock assemblies.
- Excellent interpersonal skills including strong verbal and written communication skills.
- Strong leadership skills and ability to develop, train, and motivate others.
- Able to work independently and in a team environment.
- Able to work well under pressure/emergency/time sensitive situations
- Strong planning and organizational skills.
- Accepts responsibility and accountability.
- Honest and trustworthy; displays integrity
- Professional, in appearance and action
- Able to troubleshoot problems and devise creative solutions.
- Organized and detailed
Interested? APPLY NOW!!!
Requirements:
Required Education and Experience:
- High School diploma or equivalent required, Associates degree preferred.
- At least 10 years of related experience.
- Multi\-family community experience required, preferably affordable housing experience.
- Drywall, lock change, and electrical, carpentry, flooring, and plumbing experience required.
- HVAC Type I and Type II required.
- Knowledge of 3rd party government agency inspection protocol, i.e. NSPIRE, D.C. Housing Authority, State Finance Agency, etc.
- Experience leading a team required.
- Ability to calculate figures and amounts required.
- Ability to handle finances and work within a budget.
- Work effectively as a team contributor on all assignments.
- Ability to effectively present information and respond to questions from residents, co\-workers, property owners, and the general public required.
- Yardi Maintenance software experience preferred.
- Skilled in Microsoft Excel and Word and general computer skills.
- Multilingual preferred.
- Possess own hand and power tools.
- Successful completion of a background check and drug screening 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 $95K-$105K range is above 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 ($100K) sits 40% below the category median. Disclosed range: $95K to $105K.
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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