Interested in this AI/ML Engineer role at Sun Communities?
Apply Now →Skills & Technologies
About This Role
### Job Summary
The Director, Artificial Intelligence Strategy is responsible for developing and executing Sun's enterprise\-wide AI strategy, governance, and cross\-functional alignment to drive operational excellence and create competitive advantages across our portfolio of manufactured housing and RV resort communities. This role bridges business strategy and artificial intelligence implementation, serving as the strategic leader for identifying, evaluating, and implementing AI and machine learning solutions that align with business objectives.
The Director, AI Strategy works collaboratively across teams to identify high\-value AI use cases, build internal capabilities, establish governance frameworks, and ensure responsible AI deployment. This role drives adoption efforts, promoting understanding and enablement across the organization so team members recognize how AI enhances their work and the organization maximizes the sustained value of its AI investments. This role will also help cultivate relationships with external AI vendors, technology partners, and industry thought leaders to keep Sun at the forefront of innovation in the real estate and hospitality sectors.
### Job Duties
- Drive and maintain a comprehensive AI strategy and roadmap aligned with Sun’s business objectives, identifying opportunities across key business functions. (Essential)
- Lead the evaluation and recommend prioritization of AI opportunities and partner with key business functions to develop and validate business case justifications for AI initiatives. (Essential)
- Drive cross\-functional team engagement to optimize operational efficiency through intelligent automation, enhance team member satisfaction, and promote informed decision\-making. (Essential)
- Establish and oversee AI governance frameworks and responsible AI practices ensuring compliance with data privacy regulations, fair housing laws, and industry standards. (Essential)
- Partner with technology team leaders to build and maintain the infrastructure, data architecture, platform capabilities, and guardrails required to support AI/ML model development, deployment, and monitoring at scale. (Essential)
- Collaborate with business leaders to identify pain points, inefficiencies, and opportunities where AI can deliver measurable value, conducting feasibility assessments and ROI analyses. (Essential)
- Promote a culture of innovation and partner with business leaders to drive consistent AI adoption practices and promote the advancement of enterprise\-wide AI programs. (Essential)
- Coordinates team member selection and development and ensures team members comply with appropriate policies and procedures.
- Foster effective leadership and communication at all organization levels.
- Manage relationships with AI technology vendors, consultants, and strategic partners, evaluating solutions and supporting negotiation of contracts that deliver optimal value.
- In partnership with the learning \& development team, build internal AI literacy and capabilities through training programs, workshops, and change management initiatives that foster an innovation\-oriented culture.
- Oversee proof\-of\-concept projects and pilot programs, establishing success metrics, monitoring performance, and scaling successful initiatives across the organization.
- Stay current with emerging AI technologies, industry trends, regulatory developments, and competitive landscape, providing thought leadership and recommendations to executive leadership.
- Support development and management of an AI strategy budget, ensuring efficient resource allocation and demonstrable return on investment.
- Establish performance metrics and reporting frameworks to track AI initiative outcomes, business impact, and value realization.
- Lead cross\-functional teams in the design and implementation of AI solutions, ensuring seamless integration with existing systems and processes.
- Lead, coach, and mentor high\-performing leaders and teams within the AI and Innovation function.
- Ensure AI solutions enhance rather than diminish the human touch that defines Sun’s resident experience objectives.
- Collaborate with others to address AI\-related risks including bias, transparency, security, and regulatory compliance.
- Other duties as assigned.
### Requirements
- Bachelor's Degree in Computer Science, Data Science, Information Systems, or Business Administration (Required)
- Master's Degree (Preferred)
- 8 years in progressive experience in AI/ML strategy (Required)
- 5 years in experience in leadership or management positions (Required)
- Professional certification(s) in AI, machine learning, or data science (e.g., AWS ML Specialty, Google Cloud ML Engineer, Microsoft Azure AI Engineer) (Strongly Preferred)
- Demonstrated expertise in artificial intelligence, machine learning, natural language processing, and related technologies
- Proven track record of successfully developing and executing enterprise AI strategies that delivered measurable business outcomes
- Proven ability to influence senior leaders and drive accountability for enterprise\-wide initiatives
- Strong understanding of AI governance, responsible AI practices, and regulatory considerations including data privacy and algorithmic fairness
- Experience in real estate, property management, hospitality, or related industries preferred
- Excellent business acumen with ability to translate technical concepts into business value and communicate effectively with non\-technical stakeholders
- Strong project management skills with experience leading cross\-functional initiatives and managing complex technology implementations
- Knowledge of data architecture, cloud platforms, MLOps, and AI development lifecycle
- Strategic thinking capabilities with ability to balance long\-term vision with short\-term execution
- Experience managing vendor relationships and evaluating enterprise technology solutions
- Strong analytical and problem\-solving skills with data\-driven decision\-making approach
- Excellent written and verbal communication skills with ability to present to senior leadership team
- Ability to drive successful organizational adoption of new technologies
- Ability to work independently, manage multiple priorities, and thrive in a fast\-paced environment
- Proficiency with AI/ML tools, platforms, and programming languages such as Python, R, TensorFlow, or similar technologies preferred
### BENEFITS
At Sun Communities, you will be part of an industry\-leading organization where you will be challenged, inspired, rewarded and transformed. We place a high priority on our team members, and this is a big part of what sets us apart. We will ask you to give us your very best every day, and will challenge you with interesting work, stretch assignments, a collaborative and supportive work environment and plenty of learning and growth. In exchange, we will reward you with great pay, advancement opportunities, paid time off, great benefits, and flexibility.
- Comprehensive Medical and Prescription coverage with 4 plan options so you can choose the plan that best meets the needs of you and your family
- Comprehensive Dental and Vision Plans
- On\-Site Fitness Center
- Voluntary Health and Dependent Care Reimbursement Accounts
- Life, Accidental Death \& Dismemberment Insurance and Dependent Life
- Short and Long\-Term Disability Coverage
- 401(k) Plan with Sun matching contribution
- Employee Assistance Program
- Identity Theft Insurance
- Legal Assistance Plan
- Pet Insurance
- Tuition Reimbursement program providing financial support to team members who further their formal education
- Vacation RV Site Discounts for team members when visiting SunRV Resorts across the nation
- Team Member Perks \& Discounts program with hundreds of discounts on things like travel, merchandise, mobile phone service, and more
- Up to six weeks of paid parental leave for the birth of a child, adoption, or placement of a child
- Paid Time Off including ten holidays, vacation, personal, sick time, bereavement and pay for jury duty
Apply for a Corporate Headquarters (HQ) position, located in the Metro Detroit, Michigan market today.
Join our Talent Community and explore Corporate Headquarters jobs at Sun Communities.
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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Sun Communities, 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 $181,170 based on 12,692 positions with disclosed compensation. Director-level AI roles across all categories have a median of $247,800.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Sun Communities AI Hiring
Sun Communities has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Southfield, MI, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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.