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Role: OnsiteMaintenance Technician
Location: Denver, CO
Community: The Barclay Towers Condominium
Pay: $30\.00 \- $32\.00 per hour
Job Type: Full Time
Typical Schedule: (40 hours per week, days TBD)
Company Summary
RealManage Elevated Onsite is a division of RealManage, a company that specializes in the management of community associations with onsite staff. Our mission is to provide the best possible lifestyle HOA management services to our partner communities by encompassing the Best People, Best Technology, and Best Service reputation of RealManage and its CiraConnect division. The RealManage Elevated Onsite professional staff has decades of experience managing age\-restricted communities, luxury high\-rise condominiums, co\-ops, urban mixed\-use, and large\-scale single\-family developments with complex amenities. Our focus is on customer service and lifestyle for the residents and the boards we serve\- ensuring that the community receives the finest management in the industry.
RealManage Elevated Onsite is a values\-based company with the following values as our guiding principles:
- Integrity: we always do the right thing.
- Respect: for our customers, employees and company; mutual respect is the cornerstone for every RealManage relationship.
- Selflessness: more than teamwork; we are part of something special and much larger than any of us.
- Personal Relationships: we are a professional services company; people do business with people they like.
- Always Improving: never satisfied, always learning, and always growing; one is either getting worse or getting better...never staying the same. At RealManage, we are always getting better.
- Join RealManage Elevated Onsite fast\-growing team where energy, teamwork, innovation, and contribution are highly valued.
- Each branch proudly serves a diverse mix of single\-family, townhome, and condominium communities. These community associations are of all sizes, from small communities to large, master\-planned communities.
RealManage has earned the prestigious Certified™ recognition from Great Place to Work®, a global authority on workplace culture, employee experience, and leadership excellence. This accolade is a testament to the positive feedback from our employees about their RealManage experience.
Community Summary
Barclay Towers is a secure, established high\-rise condominium located in the heart of LoDo. Barclay Towers features a unique year\-round roof\-top pool and a fitness center.
Role Summary
The Onsite Maintenance Technician will perform general maintenance of building and grounds at a HOA residential community, under direction of the General Manager. These daily responsibilities include, but are not limited to facility cleaning, minor maintenance and repairs on facilities, structures, equipment, sidewalks, drainage and skilled and semi\-skilled disciplines, e.g., plumbing, masonry, carpentry, flooring, irrigation, and electrical.
Responsibilities
- Perform preventive maintenance and routine maintenance.
- Ensure completion of work orders using work order system.
- General maintenance, janitorial and grounds work throughout the building.
- Periodic inspections of grounds, common area buildings and structures.
- Advising supervisor of needed repairs, improvements and safety issues.
- Understanding of Carpentry, Concrete, Doors, Drywall, Fencing, Cleaning, Gutters, Locks, Plumbing and Painting.
Disclaimer
This description is not intended to be an exhaustive list of duties. Responsibilities may evolve based on Board direction and community needs. Reasonable accommodations may be made to enable qualified individuals to perform the essential functions of this position.
Qualifications
- 2\+ years of maintenance experience preferred
- Experience with boiler and chiller systems
- Experience with Carpentry, Concrete, Doors, Drywall, Fencing, Plumbing and Painting required
- Experience with Cleaning, Locks and Gutters highly desired
- Must be able to speak, read and write English. Bilingual a plus.
- Must be a proficient problem\-solver
- Must know how to use tools, supplies, materials, chemicals in a manner that does not endanger self, other employees, residents, the environment or the public in general
- Experience and skills with simple electric maintenance is a plus, but not necessary
- Pool maintenance experience is a plus, but not necessary
Physical Requirements
- Ability to sit for prolonged periods at a desk and work on a computer.
- Ability to occasionally stand, walk, bend, or reach as needed.
- Ability to lift or move objects up to 10–15 pounds (e.g., files, office supplies).
- Manual dexterity to operate a computer keyboard, mouse, telephone, and other office equipment.
- Visual acuity to read printed materials, spreadsheets, and computer screens.
- Hearing and speech ability to communicate effectively in person, by phone, and in virtual meetings.
- Ability to work in a standard office environment with moderate noise levels.
- Ability to work a standard schedule, with occasional extended hours as required.
Pay
$30\.00 \- $32\.00 per hour
Benefits Include
- Medical Insurance \- Company will pay the premium for Employee Only Tier on the HSA plan
- Dental Insurance
- Vision Insurance
- Life and Disability Insurance
- HSA (Required High\-Deductible Medical Plan to be eligible)
- FSA account for health\-related expenses
- FSA account for dependent care expenses
- Education Reimbursement for industry related classes
- 401K match after 1 year
- Employee Assistance Program (EAP)
- 9 paid holidays and 2 floating holidays
EEO \& Values Statement
RealManage is a values‑based, equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Salary Context
This $62K-$66K 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 RealManage, 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 $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 ($64K) sits 61% below the category median. Disclosed range: $62K to $66K.
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.
RealManage AI Hiring
RealManage has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $66K - $66K.
Location Context
AI roles in Denver pay a median of $198,000 across 169 tracked positions. That's 8% above the national 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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