Interested in this AI/ML Engineer role at Presbyterian Healthcare Services?
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About This Role
Location Address:
9521 San Mateo NE Albuquerque, NM 87113\-2237
Compensation Pay Range:
Minimum Offer $87,526\.40 Maximum Offer $149,032\.00 Now Hiring: Remote AI Automation DeveloperSummary:
Build your Career. Make a Difference. Presbyterian is hiring a skilled AI Automation Developer. We are seeking an experienced AI Automation Architect to lead the design, development, and implementation of enterprise automation solutions using UiPath, Microsoft Power Automate, and Microsoft Copilot Studio. The ideal candidate will combine deep technical expertise with architectural leadership to deliver intelligent automation solutions that improve operational efficiency, enhance user experiences, and accelerate digital transformation within a healthcare environment.
This role requires hands\-on development experience, solution architecture expertise, and the ability to work closely with business stakeholders, IT teams, clinical and operational leaders, and enterprise architects to define and implement scalable AI\-driven automation strategies that improve patient, provider, and employee experiences. Type of Opportunity: Full time Job Exempt: Yes Job is based: Reverend Hugh Cooper Administrative Center Work Shift: Days (United States of America)
Responsibilities:
This position has full technical knowledge of all phases of applications systems analysis. Responsible for quality assurance review. Acts as project leader for projects with small budgets or limited duration
- Design end\-to\-end intelligent automation solutions using UiPath, Power Automate, and Copilot Studio.
- Define enterprise automation architecture, standards, governance, and best practices.
- Develop and deploy scalable RPA, workflow automation, and AI\-powered conversational solutions.
- Design and implement integrations with enterprise platforms and applications, including Epic, Salesforce, Genesys, Microsoft 365, ERP systems, CRM platforms, REST APIs, databases, and other line\-of\-business applications.
- Design AI\-enabled automations using Large Language Models (LLMs), Microsoft Copilot capabilities, AI Builder, and intelligent document processing.
- Partner with clinical, operational, and business stakeholders to identify and prioritize automation opportunities that improve efficiency, quality, and user experience.
- Lead technical discovery sessions, solution design workshops, and architecture reviews.
- Mentor and guide automation developers on development standards and reusable components.
- Collaborate with security, infrastructure, application, and integration teams to ensure automation solutions are secure, scalable, reliable, and compliant with healthcare regulations and enterprise architecture standards.
- Monitor automation performance and drive continuous optimization and operational excellence.
- Evaluate emerging AI and automation technologies and recommend enhancements to the enterprise automation roadmap.
Preferred Qualifications:
- Experience implementing intelligent automation within a healthcare provider or payer organization.
- UiPath Advanced Developer and/or Solution Architect certification.
- Microsoft Power Platform certifications.
- Experience with Azure AI Services, Azure OpenAI, AI Builder, Microsoft Fabric, or other AI platforms.
- Experience with process mining, task mining, document understanding, and intelligent document processing.
- Experience establishing enterprise automation governance and contributing to an Automation Center of Excellence (CoE).
Certifications:
- UiPath Certified Professional (Advanced Developer Professional or equivalent)
- Microsoft Certified: Power Platform Functional Consultant Associate (PL\-200\) or Power Platform Developer Associate (PL\-400\)
- Microsoft Copilot Studio certification or demonstrated hands\-on experience designing and implementing Copilot Studio solutions (required until formal certification is available)
Hybrid: In office expected for individuals within 60 Miles of Albuquerque every Tues, Wed, Thurs.
Remote: Open to remote applicants in the United States, except for the following states: California, Illinois, North Dakota, New York, Ohio, Washington and Wyoming
Qualifications:
- Bachelor s degree in related technical/business area plus 6 years of IT or business experience. 6 years of additional experience can be substituted in lieu of degree
- Expert\-level experience with UiPath development and solution architecture.
- Strong experience with Microsoft Power Automate (Cloud and Desktop).
- Hands\-on experience building copilots and AI agents using Microsoft Copilot Studio.
- Proven experience in integrating automation solutions with enterprise platforms such as Epic, Salesforce, Genesys, Microsoft 365, Azure services, SQL Server, REST APIs, and other enterprise applications.
- Experience in the healthcare industry, including knowledge of clinical and operational workflows, electronic health records (EHR), revenue cycle, patient access, or contact center operations.
- Familiarity with healthcare data privacy, security, and regulatory requirements, including HIPAA.
- Strong understanding of AI, Generative AI, Large Language Models (LLMs), prompt engineering, and intelligent automation.
- Strong analytical, problem\-solving, communication, and stakeholder management skills.
All benefits\-eligible Presbyterian employees receive a comprehensive benefits package that includes medical, dental, vision, short\-term and long\-term disability, group term life insurance and other optional voluntary benefits.
Wellness
Presbyterian's Employee Wellness rewards program is designed to provide you with engaging opportunities to enhance your health and activate your well\-being. Earn gift cards and more by taking an active role in our personal well\-being by participating in wellness activities like wellness challenges, webinar, preventive screening and more.
Why work at Presbyterian?
As an organization, we are committed to improving the health of our communities. From hosting growers' markets to partnering with local communities, Presbyterian is taking active steps to improve the health of New Mexicans.
About Presbyterian Healthcare Services
Presbyterian exists to improve the health of patients, members, and the communities we serve. We are locally owned, not\-for\-profit healthcare system of nine hospitals, a statewide health plan and a growing multi\-specialty medical group. Founded in New Mexico in 1908, we are the state's largest private employer with nearly 14,000 employees \- including more than 1600 providers and nearly 4,700 nurses.
Our health plan serves more than 580,000 members statewide and offers Medicare Advantage, Medicaid (Centennial Care) and Commercial health plans.
*AA/EOE/VET/DISABLED. PHS is a drug\-free and tobacco\-free employer with smoke free campuses.*
We're Determined to Support New Mexico's Well\-Being \| Presbyterian Healthcare Services
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Salary Context
This $87K-$149K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Presbyterian Healthcare Services, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($118K) sits 45% below the category median. Disclosed range: $87K to $149K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Presbyterian Healthcare Services AI Hiring
Presbyterian Healthcare Services has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Albuquerque, NM, US. Compensation range: $149K - $149K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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