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About This Role
Love + medicine is who we are, it's what we do, it's why people want to work here. If you’re looking for a job to love, apply today.
Scheduled Weekly Hours:
40 We’re not just filling positions, we’re building careers. At Emplify Health, we care for our teams, while they care for their communities. Whether you are just starting out or looking for a change, Emplify Health supports you now and into the future. Join us and find out how a little empathy changes everything.
We are seeking an innovative Artificial Intelligence Software Engineer to join our Enterprise Analytics team and help bring AI-driven solutions from concept to reality.
Our Enterprise Analytics team is committed to improving health and wellbeing by transforming data into actionable insights and empowering those we serve to meet their information and decision-making needs. In this role, you'll build software that solves real business challenges across the organization, rapidly developing and testing new ideas, often leveraging AI technologies, and scaling the most impactful solutions into enterprise-wide products. You'll work closely with end users, collaborate across teams, and help shape a fast-moving, innovation-focused environment.
Main Responsibilities Include:
- Build working software from concept to production, often using AI-assisted ("vibe coding") development tools.
- Develop rapid prototypes in the team's sandbox and iterate quickly on feedback from users.
- Help move proven prototypes out of the sandbox and into enterprise-grade products that operate at scale.
- Design, develop, test, and maintain applications in cloud environments such as Microsoft Azure.
- Work directly with business and clinical users to understand a problem and confirm the solution solves it.
- Collaborate across the enterprise architecture, data, and security partners.
- Apply sound engineering practices for code quality, testing, and documentation, scaled to the governance tier of each product.
- Contribute to enterprise architecture, data pipelines, and cloud infrastructure as the work requires.
- Help define how the team works, including its tools, standards, and ways of working.
- Keep current with emerging AI and development tools and bring promising approaches back to the team.
- Follow data governance, privacy, and security requirements, including the handling of protected health information.
- Adheres to regular and predictable attendance.
Performs other job-related responsibilities as requested or assigned. *
What's Available:
- Fulltime, 80 hours biweekly (1.0 FTE)
- Schedule: Monday-Friday days
- Location: Remote eligible role; While this role offers some flexibility in work location, candidates must reside within a reasonable commuting distance of La Crosse or Green Bay, WI due to occasional on-site needs. In addition, candidates must reside in WI, MN, IA.
- Immigration sponsorship (e.g., H-1B) is not available for this position.
Starting salary of $71,700 and up, based on your relevant years of experience. *
What You Will Need:
- Education: Bachelor's degree or equivalent years of experience and education
- Experience: 2+ years of software development experience and proficiency in a variety of programing languages and integration platforms.
- Experience with Microsoft Azure or other cloud platforms.
- Exposure to AI-assisted software development tools and practices.
- Experience creating prototypes, proof-of-concepts, or innovative technology solutions.
- Familiarity with DevOps, CI/CD pipelines, testing frameworks, and modern software engineering practices.
- Strong problem-solving, communication, and analytical skills.
In addition to the rewarding work, you'll receive:
- A highly adaptable and mission-driven organization with a work environment that supports you personally and professionally and a work culture where you are valued and appreciated
- Competitive Benefits: A comprehensive and generous benefits package (Medical, Dental, Life Ins, HSA/FSA) ensuring your comfort and well-being as a valuable team member
- Substantial retirement contribution including a 401k match & annual discretionary base contribution
- Work-Life Balance: Paid Time Off (PTO) combines vacation, sick, and personal days into one balance to allow you the flexibility to use your time off as you need
- Professional Development: Support for your career growth through Professional Development Opportunities, our Tuition Investment Program, and our Career Development Center
- Additional Employee Discounts and Perks Other benefits include a Wellness program with incentives, employer-paid life insurance and AD&D, optional short-term and long-term disability coverage, an employee assistance program, identity theft protection, pet insurance, Inspire & Celebrate colleague recognition and rewards program, a discount program, and more!
If you are looking to be a part of a stable and growing mission-driven organization, this may be the right opportunity for you!
PRACTICES AND PROMOTES BEHAVIOR CONSISTENT WITH THE MISSION, VISION AND VALUES :
Mission :
Together, we inspire your best life by relentlessly caring, learning and innovating.
Vision :
Leading with love, we courageously commit to a future of healthy people and thriving communities.
Values:
Belonging, Respect, Excellence, Accountability, Teamwork, Humility
Emplify Health is comprised of two of the Midwest’s most respected healthcare systems, Bellin Health and Gundersen Health System. Once neighbors, we are now partners, united in our mission to provide exceptional care to our communities. As a not-for-profit, patient-centered healthcare network, we have headquarters in Green Bay and La Crosse, Wisconsin. Our extensive network includes 11 hospitals and more than 100 clinics, serving 67 cities and rural communities across Wisconsin, Iowa, Minnesota and Michigan’s Upper Peninsula. With over 4,500 dedicated nurses and providers, we are committed to delivering primary, specialty and emergency care, along with innovative medical education programs. Join us in making a meaningful difference in the lives of our patients and communities.
I f you need assistance with any portion of the application or have questions about the position, please contact [email protected] or call 608-775-0267.
We inspire your best life by relentlessly caring, learning and innovating. This is our purpose. Together with our values — belonging, respect, excellence, accountability, teamwork and humility — our pillars set our foundation and our future.
Equal Opportunity Employer
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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Emplify Health, 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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Emplify Health AI Hiring
Emplify Health has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span WI, US, Green Bay, WI, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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