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About This Role
Description
Role Summary
WTW is navigating a period of significant, sustained transformation shaped by global market shifts, advances in technology, AI and automation, and the evolving expectations of our colleagues and clients. Corporate Marketing is embedding AI, automation and data more deeply into how work gets done, creating a unique opportunity to help redesign marketing workflows for greater speed, quality and impact.
This is a hands-on, individual contributor role for someone who combines strong marketing knowledge with proven experience implementing and developing AI and automation solutions for marketing or similar commercial teams. Reporting to the Head of Digital Marketing, this role will help turn the Corporate Marketing AI roadmap into practical, adopted workflow improvements across brand and content quality, creative asset production, campaign delivery, digital marketing, events, intake, approvals, reporting and analytics.
Working as part of the broader Marketing and Communication (M&C) AI and automation capability – alongside a Shared AI Solutions Developer and the AI and Automation Manager, Corporate Communication – this role will partner with Corporate Marketing, Segment Marketing, IT, Sales Operations, Analytics and external vendors to understand current workflows, diagnose friction and assess AI and automation capabilities across the MarTech stack, including Adobe, Marketo, Sitecore, Wrike, Cvent, Power BI and Microsoft 365.
Responsibilities
- Translate the Corporate Marketing AI and automation roadmap into practical, adopted workflows that simplify how marketing work gets done and reduce manual effort.
- Help identify and prioritize workflow improvement opportunities across brand and content quality, creative asset production, campaign delivery, digital marketing, events, intake, approvals, reporting and analytics.
- Partner with Corporate Marketing, Segment Marketing, IT, Sales Operations, Analytics and external vendors to understand current workflows, diagnose friction and design more effective ways of working within Corporate Marketing's platforms, standards and processes.
- Assess AI and automation capabilities across the MarTech stack – including Adobe, Marketo, Sitecore, Wrike, Cvent, Power BI, Microsoft 365 and other vendor tools – to reduce duplication, improve self-service and support better planning decisions.
- Work closely with the Shared AI Solutions Developer to translate workflow reviews and business requirements into practical, technically sound solutions, providing marketing context and prioritization to guide build decisions.
- Partner with the AI and Automation Manager, Corporate Communication to share learnings, avoid duplication of effort and maintain a consistent approach to AI and automation across M&C.
- Help marketers use data, trends and performance insight to improve future content and campaign decisions.
- Support adoption through simple guidance, playbooks, training materials and benefit tracking so teams can see what has changed, how to use it and what value it delivers.
- Champion innovative approaches to AI, automation, analytics and emerging technologies to strengthen marketing effectiveness and colleague experience.
- Establish measures of success for specific marketing efforts– including reduced process complexity, improved cycle times, increased self-service and reduced manual effort – and report progress to the Head of Digital Marketing, the Global Marketing and Communication Operations Lead and Corporate Marketing leadership.
- Build trusted relationships across Corporate Marketing, Segment Marketing leadership, IT, Sales Operations, Analytics and external vendors.
- Maintain external benchmarking and market insight on AI, automation and MarTech trends, bringing best practice into Corporate Marketing's roadmap and priorities.
- Model WTW values – client focus, teamwork, respect, excellence and integrity.
Qualifications
- Strong, well-rounded marketing knowledge, including some combination of brand, content, creative production, campaign delivery, digital marketing and/or marketing operations.
- Proven experience implementing and developing AI and automation solutions for marketing or similar commercial teams, including workflow redesign, process simplification and tool evaluation.
- Fluency in how AI and automation are reshaping marketing work, with experience leveraging AI-enabled tools (such as Copilot or equivalent) to elevate quality, efficiency and effectiveness.
- Working knowledge of the MarTech landscape (e.g., Adobe, Marketo, Sitecore, Wrike, Cvent, Power BI, Microsoft 365) and the ability to assess capabilities and identify practical improvement opportunities.
- Ability to translate business needs into clear requirements for a technical developer to build against; comfortable partnering closely with a solutions developer without formal people management responsibility.
- Strong analytical mindset – adept at using data, benchmarks and metrics to identify friction, prioritize opportunities and measure impact.
- Excellent stakeholder management and relationship-building skills; able to build trust and influence marketing leaders and colleagues without formal authority.
- Highly organized, detail-oriented and adaptable; skilled at managing multiple concurrent priorities across geographies and time zones.
- Experience designing adoption support materials, including simple guidance, playbooks and training content.
- Aptitude to synthesize direction, navigate ambiguity and prioritize actions from a variety of stakeholders.
- Bachelor's degree or equivalent experience in marketing, communication, business, technology or a related field.
- Experience working within a large, complex, global organization preferred.
Location: United States (Remote)
Note: Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity
Compensation and Benefits
Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role.
Compensation
The base salary compensation range being offered for this role is $120,000-$150,000 USD annually. This role is also eligible for an annual short-term incentive bonus.
Company Benefits
WTW provides a competitive benefit package which includes the following (eligibility requirements apply):
- Health and Welfare Benefits: Mental health/emotional wellbeing (including Employee Assistance Program), medical (including prescription drug coverage and fertility benefits), dental, vision, Health Savings Account, Commuter Accounts, Health Care and Dependent Care Flexible Spending Accounts, company-paid life insurance, supplemental life insurance, AD&D, group accident, group critical illness, group legal, identify theft protection, wellbeing program, adoption assistance, surrogacy assistance, auto/home insurance, pet insurance and other work/life resources
- Leave Benefits: Paid holidays, annual paid time off (includes state/local paid leave where required), company-paid disability (short-term and long-term disability), other leaves (e.g., bereavement, FMLA, ADA, jury duty, military leave, and Parental and Adoption Leave), Paid Time Off
- Retirement Benefits: Qualified contributory pension plan (if eligible) and 401(k) plan with annual nonelective company contribution. Non-qualified retirement plans available to senior level colleagues who satisfy the plans’ eligibility requirements
Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records.
This position will remain posted for a minimum of three business days from the date posted or until sufficient/appropriate candidate slate has been identified.
EOE, including disability/vets
Salary Context
This $120K-$150K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At WTW, 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 $212,040 based on 13,780 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($135K) sits 36% below the category median. Disclosed range: $120K to $150K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
WTW AI Hiring
WTW has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Charlotte, NC, US. Compensation range: $150K - $150K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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