Interested in this AI/ML Engineer role at Wiley?
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Job Description:
We believe in bold ideas, diverse perspectives, and the drive to transform knowledge into impact. Here, your curiosity fuels progress, your voice shapes innovation, and your ambition helps redefine what’s possible within science and learning. We are a culture that obsesses over impact, challenges, and drives what’s next to power infinite possibilities for our customers, colleagues and society at large.
About the Role:
As Executive Assistant, you will provide reliable, well\-organized executive support that enables the SVP to focus time and energy where it matters most. Requirements are targeted: calendar and travel management, coordination with ELT\-level EAs across the organization, and ensuring in\-person engagements — meetings, and off\-sites — are set up and run seamlessly. The role carries inherent exposure to highly confidential information, which requires consistent discretion and professional judgement.
As Chief of Staff Associate, you will work directly with the VP, Business Operations and Chief of Staff ( CoS ) You will be a genuine thought partner: given minimal context, you will be expected to build out, complete, and in some cases own work that would otherwise sit with the CoS.
Job Responsibilities :
Executive Support
- Manage the SVP’s calendar end\-to\-end, including prioritization of competing demands and proactive horizon planning.
- Coordinate domestic and international travel arrangements, including itineraries, logistics , and expenses.
- Process expenses accurately and in line with Wiley policy.
- Act as primary liaison with ELT\-level EAs to align calendars, schedule cross\-functional meetings, and coordinate logistics for joint sessions.
- Own end\-to\-end logistics for in\-person engagements — meeting rooms, catering, materials, AV — ensuring nothing falls through.
- Handle confidential communications and correspondence with the professionalism and discretion expected at SVP level which may include acting with imperfect or no information.
Chief of Staff Associate Support
- Support CoS on range of strategic and operational priorities by building out details and driving execution across the BU.
- Develop an understanding of the BU strategic framework and use this context to sharpen your own outputs and anticipate needs.
- Receive briefs, incomplete drafts, or minimal context and translate them into polished, audience\-ready outputs with limited follow\-up.
- Support preparation of communications, briefing notes, presentations, and strategic documents for the SVP, AIDA leadership, and broader Wiley stakeholders.
- Assist with tracking and monitoring key priorities, actions, and commitments across the business units’ portfolio.
- Coordinate preparation for key governance rhythms ( e.g. including leadership team meetings, off\-sites, and operating reviews) covering logistics , pre\-reads, and follow\-up actions.
- Over time, take on increasing ownership of CoS workstreams as trust and capability develop.
Required Qualifications:
- Proven experience supporting a senior executive at SVP or C\-suite level, including complex calendar and travel management, in a fast\-paced, ambiguous, and changing environment.
- High level of discretion — comfortable handling confidential information as a matter of course.
- Exceptional written communication skills: able to draft, structure, and edit documents quickly and to a high standard.
- Strong organizational and prioritization skills — able to manage multiple competing demands without losing focus.
- Analytical and structured thinking: able to take ambiguous input and produce clear, logical output.
- Confident working with minimal direction and completing tasks without step\-by\-step guidance.
- Proven ability to build strong working relationships with senior stakeholders and peer coordinators.
- Demonstrated use of AI in daily work
Preferred Qualifications:
- Experience working in or alongside a Chief of Staff, strategy, or business operations function.
- Exposure to fast growing and scaling environments.
- Familiarity with program or portfolio tracking tools and executive communication platforms.
- Desire to grow this into a strategic role.
We power infinite possibilities.
For more than 200 years, we've transformed knowledge into discoveries that shape the world. Today, our global team of innovators, creators, and experts is driving what's next in science, education, and publishing—creating impact that reaches everywhere.
We're not just observers of progress. We're the ones accelerating scientific breakthroughs, advancing learning, and sparking innovation that redefines entire fields and improves lives.
Here, your talent matters. Your ideas have room to grow. And your work creates breakthroughs that can change everything.
Wiley is an equal opportunity/affirmative action employer. We evaluate all qualified applicants and treat all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, protected veteran status, genetic information, or based on any individual's status in any group or class protected by applicable federal, state or local laws. Wiley is also committed to providing reasonable accommodation to applicants and employees with disabilities. Applicants who require accommodation to participate in the job application process may contact tasupport@wiley.com for assistance.
We are proud that our workplace promotes continual learning and internal mobility. Our values support courageous teammates, needle movers, and learning champions all while striving to support the health and well\-being of all employees. We offer meeting\-free Friday afternoons allowing more time for heads down work and professional development, and through a robust body of employee programing we facilitate a wide range of opportunities to foster community, learn, and grow.
We are committed to fair, transparent pay, and we strive to provide competitive compensation in addition to a comprehensive benefits package. The range below represents Wiley's good faith and reasonable estimate of the base pay for this role at the time of posting roles in the United Kingdom, Canada, USA, Austria, Czechia, Denmark, France, Greece, Italy, Netherlands, Romania, or Spain. It is anticipated that most qualified candidates will fall within the range, however the ultimate salary offered for this role may be higher or lower and will be set based on a variety of non\-discriminatory factors, including but not limited to, geographic location, skills, and competencies.
When applying, please attach your resume/CV to be considered.
Salary Range:
73,400 USD to 102,600 USD\&\#xa;\&\#xa;\#LI\-JG1
Salary Context
This $73K-$102K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Wiley, 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 in Demand for This Role
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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($88K) sits 60% below the category median. Disclosed range: $73K to $102K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Wiley AI Hiring
Wiley has 2 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer. Based in Hoboken, NJ, US. Compensation range: $102K - $173K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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