Interested in this AI/ML Engineer role at US News & World Report?
Apply Now →Skills & Technologies
About This Role
U.S. News & World Report is a multifaceted digital media company dedicated to helping citizens, consumers, business leaders and policy officials make important decisions in their lives. We publish independent reporting, rankings, data journalism and advice that has earned the trust of our readers and users for 90 years. Our platforms on usnews.com include Education, Health, Money, Travel, Cars, News, Real Estate, Careers and Insurance.
We reach millions of people monthly during moments when they are most in need of expert advice and motivated to act on that advice directly on our platforms. Our signature franchises include our ?Best? series of consumer guides on colleges, graduate schools, hospitals, diets, cars, financial services and more. These guides provide an easy-to-digest list for consumers to better understand and compare when making their decisions. We continue to publish annual guides of the authoritative Best Colleges and Best Hospitals rankings on our website and in print. And our U.S. News Live flagship conferences highlight important national conversations such as Healthcare of Tomorrow .
We believe in having a broad range of talent and backgrounds at U.S. News. We strive to maintain a welcoming and inclusive workplace where everyone is given an opportunity to succeed and contribute to their fullest.
Your role in helping us shape the future:
U.S. News empowers everyone to thrive. We are looking for an enthusiastic Full Stack Senior Software Developer with an interest in building dynamic, data-driven products. We value an ?AI-first? mindset, requiring a positive attitude toward using AI tools to maximize efficiency and workflows. The developers at U.S. News have a great deal of independence and a minimum of overhead. By leveraging the latest AI-coding tools, React, Python, Amazon Web Services, Google BigQuery, data science toolkits and other modern technologies, you?ll be driving a major transformation within U.S. News.
The successful candidate will become an influential member of a passionate, friendly and growing team that creates web applications which reach millions of visitors monthly. Developers typically see applications through from beginning to end, working directly with product owners to create, implement, upgrade, optimize and test features and projects.
Are you up to the challenge?
Join the Hospital Data Insights engineering team on U.S. News Health: we build and operate hospital data products?including ingestion pipelines, APIs and customer-facing applications?under strict launch schedules.
This is a senior, backend- and data-heavy role. You will build and maintain Python services and PostgreSQL-backed data workflows (ETL, validation, reliability) and partner with product and methodology stakeholders when datasets or launch timelines shift. React and modern web standards matter when the application layer needs changes, but most of your impact is in data correctness, pipeline automation, and production operations ? not greenfield UI alone.
Our team uses AI-assisted development (Cursor, agents and similar tools) as part of everyday delivery?investigation, implementation, review and documentation. You will collaborate with engineers, analysts and product owners on a fast-moving Health portfolio; you will also be trusted to work through ambiguous, legacy-heavy problems calmly as release dates approach.
As a senior software developer on HDI, you will:
- Design, build and operate data pipelines and backend services that power hospital insights products
- Improve ETL automation, monitoring and data quality as volumes and module complexity grow
- Partner with engineering leadership and cross-functional stakeholders through coordinated releases (including embargo-driven launches)
- Employ an AI-first approach to investigation, implementation and code review
- Develop and maintain clean, efficient, well-tested code
- Make pragmatic architecture decisions, mentor others, and serve as a technical role model responsible for promoting the overall quality of our team and technology beyond your individual contributions
- Collaborate closely with product owners and stakeholders on product requirements to streamline and understand new feature work
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 US News & World Report, 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. Senior-level AI roles across all categories have a median of $229,300.
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.
US News & World Report AI Hiring
US News & World Report has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Washington, DC, 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.