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About This Role
Serious Medicine is what we do. Being extraordinary is who we are. Every colleague plays a key role in upholding this promise to our patients and their families.
Shift:
First Shift (United States of America) Intern - Forward Deployed AI Engineer
Build Your AI Engineering Career at Nebraska Medicine!
What if your internship gave you the opportunity to work on real AI and data challenges in healthcare—not just classroom projects? As an AI Engineer Intern , you’ll work alongside Nebraska Medicine’s AI Engineering team and experienced Palantir Forward Deployed Software Engineers, gaining hands-on experience with Palantir Foundry, Python, TypeScript, data analytics, and AI while contributing to solutions that support clinicians, staff, researchers, and patients.
You’ll have the opportunity to learn how real healthcare problems are translated into technology solutions—from understanding workflows and analyzing data to building, testing, and improving AI and analytics applications. You’ll receive coaching and mentorship while also taking meaningful ownership of project work and collaborating with technical and non-technical stakeholders.
We’re looking for a curious problem-solver who loves to learn , asks thoughtful questions, and is excited to explore what AI can do in healthcare. If you’re looking for an internship where you can grow your technical skills, develop your ability to work with real-world users, and potentially build a path toward a future Data, Analytics and AI Engineer role, come build what’s next with us!
Details: Intern - Forward Deployed AI Engineer
- Candidate must live in Nebraska or Iowa for Summer Months
- This is a hybrid position, must be able to work on campus
- Preferred consideration will be given to applicants with project management experience in information technology, industrial engineering, supply chain, or healthcare quality improvement
- Resume REQUIRED for consideration
Why Work at Nebraska Medicine?
- Together. Extraordinary. Join a team that values your skills, delivering exceptional care through collaboration.
- Leading Health Network Work with the region’s top academic health network, partnering with UNMC to transform lives through education, research, and patient care.
- Dignity and Respect: We value all backgrounds and experiences, reflecting the communities we serve.
- Educational Support Enjoy up to $5,000/year in tuition assistance, a 35% discount at Clarkson College, and career advancement opportunities with covered educational costs. Enjoy support for your personal growth within the organization, from those just starting their healthcare careers to those who are years down the path.
Be part of something extraordinary at Nebraska Medicine!
Join Nebraska Medicine as an AI Engineer Intern and gain hands-on experience working in Palantir Foundry alongside our AI engineering team and contracted Palantir Forward Deployed Software Engineers. In this role, you’ll apply your software skills in a cutting-edge data platform, use AI and machine learning on real hospital challenges, collaborate with executives and frontline staff, and contribute to projects that directly impact clinicians, staff, and patients. This is a unique opportunity to build technical and interpersonal skills in a mission-driven environment—while having autonomy over your work without the overhead of a traditional software team.
Details: Intern - Forward Deployed AI Engineer
- Candidates must reside in NE or IA during summer months
- Preferred consideration will be given to applicants with familiarity with enterprise software like Palantir, Dataiku, or DataRobot
Resume REQUIRED for consideration *
Why Work at Nebraska Medicine?
- Together. Extraordinary. Join a team that values your skills, delivering exceptional care through collaboration.
- Leading Health Network Work with the region’s top academic health network, partnering with UNMC to transform lives through education, research, and patient care.
- Dignity and Respect: We value all backgrounds and experiences, reflecting the communities we serve.
- Educational Support Enjoy up to $5,000/year in tuition assistance, a 35% discount at Clarkson College, and career advancement opportunities with covered educational costs. Enjoy support for your personal growth within the organization, from those just starting their healthcare careers to those who are years down the path.
Be part of something extraordinary at Nebraska Medicine!
As an AI Engineer Intern, you will work closely with our Data, Analytics, and AI teams to assist in the development and deployment of AI-driven solutions within our organization. You will gain hands-on experience with tools like Palantir, Python, SQL, and Typescript, and collaborate on building data workflows, conducting analyses, and supporting AI integration projects. This role is designed as a steppingstone into a future Data, Analytics, and AI Engineer position, with mentorship and development opportunities.
Required Qualifications: Intern - Forward Deployed AI Engineer
- Currently pursuing a bachelor’s degree in computer science, Data Science, Engineering, or a related field required.
- Familiarity with programming languages such as Python, SQL, and Typescript is a plus required.
- Strong interest in data analytics, AI, and software development required.
- Basic understanding of data structures, data modeling, and analytical techniques required.
- Demonstrated problem-solving skills and ability to work independently and as part of a team required.
Effective communication skills to articulate technical concepts to diverse audiences required. *
Preferred Qualifications: Intern - Forward Deployed AI Engineer
- Exposure to data analytics platforms and visualization tools such as Tableau, Power BI, or similar preferred.
- Curiosity about AI concepts, including machine learning, natural language processing, and large language models preferred.
- Familiarity with enterprise software like Palantir, Dataiku, or DataRobot is advantageous preferred.
- Prior experience in collaborative projects or internships related to data or AI preferred.
- Certification or coursework in data science, AI, or related fields is a plus preferred.
Nebraska Medicine is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, sex, age, national origin, disability, genetic information, sexual orientation, gender identity and protected veterans’ status.
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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Nebraska Medicine, 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 $212,000 based on 11,857 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,408.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Nebraska Medicine AI Hiring
Nebraska Medicine has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Omaha, NE, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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