Interested in this AI/ML Engineer role at Syufy Enterprises?
Apply Now →Skills & Technologies
About This Role
ABOUT US:
SyRES PROPERTIES is a privately held real estate investment and development firm focused on the acquisition, new development and asset management of institutional quality multifamily residential properties. Our development pipeline and acquisition prospects are concentrated in the western United States including California, Oregon, Washington and Nevada. We are actively looking for qualified professionals who will help execute the company’s future growth strategy.
POSITION SUMMARY:
The Maintenance Supervisor reports to the Sr. Director, Facilities and is responsible for the overall maintenance staff on site. This person is responsible for being hands on and completing the work orders on a timely basis. As a leader of our maintenance team, you'll play a crucial role in ensuring the operational excellence, curb appeal and resident satisfaction of the apartment community.
RESPONSIBILITIES:
- Work with Community Manager to coach the maintenance team and monitor the team’s performance against community goals.
- Assist in training the maintenance team staff on maintenance, safety and customer service procedures.
- Assist Community Manager with annual budget and making recommendations on bids
- Adhere to and enforce compliance of all state law regulations and SyRES policies and procedures relating to the apartment community.
- Perform and oversee routine preventative maintenance on equipment and systems.
- Participate in an on\-call rotation to provide after\-hours emergency maintenance services as needed.
- Ensure compliance with safety regulations and operational standards in all maintenance activities.
- Ability to drive locally for business purposes pertaining to property management maintenance.
- Other duties as assigned.
QUALIFICATIONS:
- Minimum of 5\+ years of hands\-on experience in apartment maintenance or equivalent.
- 5\+ years of multi\-family industry experience preferred.
- 5 years in a supervisory role strongly preferred.
- Able to handle tools and power equipment, such as drills, saws, grinders, electrical testers, HVAC systems, and plumbing tools. including proficiency in plumbing, electrical systems, HVAC, appliance repair, and general carpentry
- EPA Section 608 Certified HVAC Technician and Certified Pool Operator (CPO) preferred, demonstrating technical expertise in property systems and amenities management.
- Demonstrates excellent organizational and time management skills, effectively prioritizing tasks to meet deadlines and maintain operational efficiency
- Skilled in coordinating with vendors and efficiently scheduling maintenance and repair work to ensure timely completion and minimal disruption to operations.
- Proficiency in Microsoft Office Applications strongly preferred.
- Strong troubleshooting abilities to quickly assess and resolve maintenance issues, ensuring minimal disruption to residents.
- Excellent verbal and written communication skills to interact with residents, team members, and vendors effectively.
- A passion for delivering exceptional service to residents and creating a positive living experience.
- Willingness to work a flexible schedule and participate in an on\-call rotation to handle apartment maintenance emergencies.
PHYSICAL AND ENVIROMENTAL REQUIREMENETS:
- Occasional bending, kneeling, and lifting up to 50 lbs
- Frequent sitting and occasional standing, walking, reaching
- Noise level may be moderate to high at times
BENEFITS/PERKS:
- Hourly wage based on relevant experience to the role. Full\-time hours.
- Eligible for annual bonus based on operational metrics and leadership competencies.
- PTO.
- Full benefits package (Medical, dental, vision, cell phone reimbursement)
- 401K with dollar for dollar match up to 4%.
*PRIVACY NOTICE TO CALIFORNIA JOB APPLICANTS*
Syufy Enterprises and/or any affiliated entities (collectively, the “Company” or “we”) provide this California Privacy Notice (“Notice”) to describe our privacy practices with respect to our collection of Personal Information as required under the California Consumer Privacy Act (“CCPA”) as amended by the California Privacy Rights Act (“CPRA”). This Notice applies only to job applicants and candidates for employment who are residents of the State of California (“Consumers”) and from whom we collect “Personal Information” as defined in the CCPA. We provide you this Notice because under the CCPA, California residents who are job applicants qualify as Consumers. For purposes of this Notice, when we refer to Consumers, we mean you only to the extent you are a job applicant who resides in California.
1\. Information We Collect from or About Job Applicants
We may directly or indirectly collect Personal Information from you in a variety of different situations and using a variety of different methods, including, but not limited to, on our website, your mobile device, through email, in physical locations, through written applications, through the mail, and/or over the telephone. Generally, we may collect, receive, maintain, and use the following categories of Personal Information, depending on the particular purpose and to the extent permitted under applicable law:
Personal Identifiers \& Contact Information: Name, alias, home, postal or mailing address, email address, telephone number.
Pre\-Hire, Employment, and Education History Information: Information provided in your job application or resume including prior job experience and/or positions held, your salary expectations, educational history or records of degrees and/or certifications, information gathered as part of reference checks, information recorded in job interview notes by persons conducting job interviews for the Company, information contained in candidate evaluation records and assessments, information in work product samples you provided, and voluntary disclosures by you.
Inferences: Based on analysis of the personal information collected, we may develop inferences regarding job applicants’ predispositions, behavior, attitudes, intelligence, abilities, and aptitudes for purposes of recruiting and hiring assessments and decisions.
Of the above categories of Personal Information, the following are categories of Sensitive Personal Information the Company may collect:
1\. Personal Identifiers
Personal Information does not include:
- Publicly available information from government records.
- Information that a business has a reasonable basis to believe is lawfully made available to the general public by the job applicant or from widely distributed media.
- Information made available by a person to whom the job applicant has disclosed the information if the job applicant has not restricted the information to a specific audience.
- De\-identified or aggregated information.
2\. How We Use Personal Information and Sensitive Personal Information
The Personal Information and Sensitive Personal Information we collect, and our use of Personal Information and Sensitive Personal Information, may vary depending on the circumstances. This Notice is intended to provide an overall description of our collection and use of Personal Information and Sensitive Personal Information. Generally, we may use or disclose Personal Information and Sensitive Personal Information we collect from you or about you for one or more of the following purposes:
- To fulfill or meet the purpose for which you provided the information. For example, if you share your name and contact information to apply for a job with the Company, we will use that Personal Information in connection with your candidacy for employment.
- To comply with local, state, and federal law and regulations requiring employers to maintain certain records (such as immigration compliance records, travel records, personnel files, wage and hour records, payroll records, accident or safety records, and tax records), as well as local, state, and federal law, regulations, ordinances, guidelines, and orders relating to COVID\-19\.
- To evaluate, make, and communicate decisions regarding your job application and candidacy for employment.
- To communicate with you regarding your candidacy for employment.
- To evaluate and improve our recruiting methods and strategies.
- To evaluate job applicants and candidates for employment or promotions.
- To obtain and verify employment references.
- To engage in corporate transactions requiring review or disclosure of job applicant records subject to non\-disclosure agreements, such as for evaluating potential mergers and acquisitions of the Company.
- COVID\-19 RELATED PURPOSES
a. To reduce the risk of spreading the disease in or through the workplace.
b. To protect job applicants and everyone else at Company workplaces from exposure to COVID\-19\.
c. To comply with local, state, and federal law, regulations, ordinances, guidelines, and orders relating to COVID\-19, including applicable reporting requirements.
d. To facilitate and coordinate pandemic\-related initiatives and activities (whether Company\-sponsored or through the U.S. Center for Disease Control and Prevention, other federal, state and local governmental authorities, and/or public and private entities or establishments, including vaccination initiatives).
e. To permit contact tracing relating to any potential exposure.
f. To communicate with job applicants and other consumers (including employees and visitors to our workplace) regarding potential exposure to COVID\-19 and properly warn others who have had close contact with an infected or symptomatic individual so that they may take precautionary measures, help prevent further spread of the virus, and obtain treatment, if necessary.
10\. To evaluate, assess, and manage the Company’s business relationship with vendors, service providers, and contractors that provide services to the Company related to recruiting or processing of data from or about job applicants.
11\. To improve job applicant experience on Company computers, networks, devices, software applications or systems, and to debug, identify, and repair errors that impair existing intended functionality of our systems.
12\. To protect against malicious or illegal activity and prosecute those responsible.
13\. To prevent identity theft.
14\. To verify and respond to consumer requests from job applicants under applicable consumer privacy laws.
3\. Sale/Sharing of Information to Third Parties
The Company does not sell your Personal Information or Sensitive Personal Information for any monetary or other valuable consideration. The Company does not share your Personal Information or Sensitive Personal Information for cross\-context behavioral advertising.
4\. Access to Privacy Policy
For more information, you can request a copy of the Company’s Privacy Policy by sending an e\-mail to hr@150pelican.com.
5\. Data Retention:
Syufy Enterprises retains information for as long as reasonably necessary for the purposes for which it was collected, or as otherwise permitted or required by law. In deciding how long to retain each category of Personal Information that we collect, we consider many criteria, including, but not limited to: the business purposes for which the Personal Information was collected; relevant federal, state and local recordkeeping laws; applicable statute of limitations for claims to which the information may be relevant; and legal preservation of evidence obligations.
By submitting my resume and/or application, I acknowledge and confirm that I have received and read and understand this Notice and I hereby authorize and consent to the Company’s use of the Personal Information and Sensitive Personal Information it collects, receives or maintains for the business purposes identified above.
Salary Context
This $83K-$95K 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 Syufy Enterprises, 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 ($89K) sits 46% below the category median. Disclosed range: $83K to $95K.
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.
Syufy Enterprises AI Hiring
Syufy Enterprises has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in South San Francisco, CA, US. Compensation range: $95K - $95K.
Location Context
AI roles in San Francisco pay a median of $244,000 across 1,059 tracked positions. That's 33% 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.