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About This Role
Quorum Services is currently seeking an innovative, proven leader who shares a passion for building and leading exceptional teams in the Healthcare industry. We are looking to develop entrepreneurial spirited leaders who appreciate the backing of an industry leading company, and mentorship from successful leaders who are simultaneously building their own companies within Quorum Services. If you are seeking an opportunity to create, innovate and lead your own company with our support, then we have the right opportunity for you!
*About the Company*
Quorum Services is a fast-paced, dynamic company that provides operational and administrative support to multiple business lines in the health care services field and more. Quorum Services currently serves four rapidly growing business lines with more than 700 employees. We are dedicated to ensuring our partners have the ultimate entrepreneurial experience and positioned to secure maximum growth within their business. Our passion, effectiveness, and efficiency places us at the forefront of other health care service providers and leaders. These operations have no corporate headquarters or traditional management hierarchy. Instead, they operate independently with support from the “Service Center,” a world-class service team that provides the centralized clinical, legal, risk management, HR, training, accounting, IT and other resources necessary to allow on-site leaders and caregivers to focus squarely on day-to-day care and business issues in their individual agencies.
Something else that sets us apart from other companies is the quality of our most valuable resources – our people! We are dedicated to living out our culture as defined by our core values, “CAPLICO”:
*Customer Second*
*Accountability*
*Passion for Learning*
*Love One Another*
*Intelligent Risk Taking*
*Celebrate*
*Ownership*
By incorporating these principles at all levels of our organization, our employees feel valued and excited about their impact on our service center team members and operational partners. Our culture fosters excellence both personally and professionally and promotes development that leads to continued success.
*About the Opportunity*
The CEO-In-Training (CIT) role is intended to prepare proven leaders for an executive Director position, overseeing a Quorum affiliated company. The CIT Program is a full time, paid executive training program that runs approx. 3-6 months, depending on level of experience and industry knowledge. Upon demonstrating competence and core values, CITs are selected to lead a local company, with the support of peers leading their own Quorum-affiliated companies.
CIT’s receive practical on-the-job training in an operational environment under the direct supervision of an experienced Executive Director/CEO. In preparation to become an Executive Director, CIT’s will be mentored by several proven leaders to gain a thorough understanding of our culture and core values, operating models, systems and what it will take to be a successful leader of a Quorum-affiliated company. The CIT program will consist of hands-on training in all roles within an operation, shadowing clinicians to learn our clinical product, administrative staff to learn the business model, and independent study of regulations and specific curriculum focused on becoming an exceptional operator. In addition, CITs are expected to take on projects and real responsibilities at their host operation and encouraged to identify opportunities and solutions as they master the fundamentals of our business.
*Duties and Responsibilities*
- The CIT will use the CIT Competency Checklist to assess strengths and weaknesses to determine their objectives.
- Meet with their preceptor (Executive Director) weekly to review CIT Competency Checklist progress.
- Become acquainted with each member of the leadership team and communicate needs and opportunities regularly.
- Observe each position within the company to gain an understanding of each person’s role, responsibilities, and best practices.
- Attend and engage in quarterly Boot Camp training(s).
- Attend and engage in weekly New Leader phone calls.
- Attend and engage in cluster calls.
- Demonstrate an ability to give and receive feedback, acting within Quorum Services core values.
- Demonstrate an ability to act and lead within Quorum Services core values. *Customer Second \* Accountability \* Passion for Learning \* Love One Another \* Intelligent Risk Taking \* Celebration \* Ownership*
- Demonstrate an ability to perform competent financial controls, including but not limited to P&L Management, Cost Management, Accounts Receivable, etc.
- Demonstrate an ability to perform competent clinical controls
- Demonstrate an ability to perform representation in the community and earn business.
The above statements are only meant to be a representative summary of the major duties and responsibilities performed by incumbents of this job. The incumbents may be requested to perform job-related tasks other than those stated in this description.
*Qualifications*
- 3-5 years proven leadership experience demonstrating successful results, required.
- Bachelor’s Degree preferred - MBA/MHA a plus.
*Additional Information*
We are committed to providing a competitive Total Rewards Package that meets our employee’s needs.
From a choice of medical, dental and vision plans to retirement savings opportunities through a 401(k), company match and various other features, we offer a comprehensive benefits package. We believe in great work and we celebrate our employees' efforts and accomplishments both locally and companywide, recognizing people daily through our Moments of Truth Program. In addition to recognition, we believe in supporting our employees' professional growth and development. We provide employees a wide range of free e-courses through our Learning Management System as well as training sessions and seminars.
*Compensation*: Based on experience.
*Type:* Full Time
*About The Quorum Services:*
Quorum Services provides resources and support in a multitude of business areas: legal, compliance, human resources, recruiting, accounting, finance, information technology (IT), learning and development, and construction. Each of these departments engage in a collective quest to develop and support our affiliates in the field so they can deliver dignified, quality healthcare experiences to our residents and the community. While the field can get support and advisement from the Quorum Services Service Center, the decision ultimately lies with the leadership team in the operation.
Job Type: Full-time
Pay: $65,474.84 - $78,851.42 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible spending account
- Health insurance
- Health savings account
- Paid time off
- Parental leave
- Tuition reimbursement
- Vision insurance
Work Location: In person
Salary Context
This $65K-$78K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Arris Healthcare, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($72K) sits 53% below the category median. Disclosed range: $65K to $78K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Arris Healthcare AI Hiring
Arris Healthcare has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Tacoma, WA, US. Compensation range: $78K - $78K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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