Interested in this AI/ML Engineer role at UL Solutions?
Apply Now →About This Role
The Corporate Communications Lead, AI and Technology, is responsible for helping UL Solutions' Corporate Communications function identify, adopt, measure and optimize technologies that enhance the company’s internal and external communications impact. This role serves as a key resource for advancing the department's AI, Generative Engine Optimization (GEO), and analytical capabilities, ultimately driving greater visibility and reputation of the UL Solutions brand across traditional and digital media channels.
Working closely with Corporate Communications leadership, this individual evaluates emerging technologies, develops measurement frameworks, identifies opportunities to improve workflows and supports the adoption of new tools and capabilities across the communications function. The role also helps advance the organization's understanding of how to influence visibility and discoverability within AI and Large Language Model (LLM)\-powered search and answer engines and supports efforts to measure and improve those outcomes.
The ideal candidate combines an understanding of communications and content ecosystems with expertise in technology, analytics and emerging digital trends. This individual is naturally curious, highly collaborative and passionate about translating insights on new technologies into tactics and strategies that help will Corporate Communications operate more effectively and deliver greater impact.
AI and GEO Leadership
- Support the development and evolution of Corporate Communications' GEO capabilities, including best practices, measurement approaches and reporting frameworks.
- Monitor and analyze trends related to AI\-powered search, answer engines and digital content discovery.
- Evaluate how communications activities influence organizational visibility within AI\-generated responses and emerging search experiences.
- Develop insights and recommendations that help improve the discoverability, visibility and effectiveness of communications content within AI\-powered environments.
- Partner with stakeholders across the organization to own and advance GEO\-related initiatives and help establish scalable approaches for measuring success.
Measurement and Insights
- Translate complex data into clear, compelling insights that support strategic decision\-making.
- Develop and maintain dashboards, reporting frameworks and measurement approaches that provide visibility into communications performance, technology adoption and GEO initiatives.
- Analyze data, trends and performance indicators to generate actionable insights and recommendations for communications leaders.
- Establish standards and methodologies for measuring workflow improvements, technology adoption, communications effectiveness and GEO outcomes.
- Develop insights and reporting that help senior leaders evaluate the impact of communications activities, technology investments and GEO initiatives.
Technology and Tools
- Lead efforts to evaluate, procure and implement new technologies and tools across the corporate communications teams to help improve the effectiveness of internal and external functions.
- Develop and scale AI\-enabled workflows supporting content development, research, planning, reporting and analysis.
- Partner with communications leaders and colleagues to identify practical applications for AI and emerging technologies across the function.
- Monitor emerging technology trends and translate opportunities into actionable recommendations, pilot programs and scalable solutions.
Operations Enablement
- Support efforts to improve communications workflows, processes and ways of working through the application of technology, automation and data\-driven insights.
- Develop resources, training materials and guidance that help colleagues adopt new tools, capabilities and best practices.
- Partner with communications leaders to scale successful technologies, workflows and operational improvements across the organization.
- Help foster a culture of experimentation, continuous learning and innovation within the communications function.
- Support initiatives that help Corporate Communications operate more effectively and deliver greater impact through smarter use of technology and data.
Education
- Bachelor's degree in Communications, Marketing, Business, Data \& Analytics, Information Systems, Technology, or a related field.
Required Experience
- 5–8 years of professional experience in communications, public relations, digital marketing, marketing technology, marketing operations, analytics, technology consulting or a related field.
- Experience evaluating, implementing or optimizing technology platforms, digital tools, workflows or business processes.
- Experience using data, analytics and reporting to generate insights and support decision\-making.
- Experience with communications measurement, content analytics, SEO, GEO or digital content performance.
- Experience developing dashboards, measurement frameworks, reporting programs or performance metrics.
- Demonstrated ability to communicate complex concepts and recommendations to both technical and non\-technical audiences.
Preferred Experience
- Experience supporting communications, marketing, content, digital or related business functions.
- Experience with artificial intelligence, automation, generative AI tools or emerging technology applications.
- Experience leading projects and initiatives involving multiple stakeholders, functions and priorities.
- Experience identifying opportunities to improve effectiveness, efficiency or business performance through technology, automation or process improvement.
- Experience evaluating emerging technologies and translating trends into practical business applications.
Knowledge, Skills and Abilities
- Knowledge of AI, GEO, digital content discovery and emerging communications technologies.
- Strong analytical, critical thinking and problem\-solving skills.
- Sharp business acumen and ability to translate findings into actionable recommendations.
- Ability to evaluate technologies and determine potential business value and applicability.
- Strong project management, organizational and prioritization skills.
- Ability to influence, collaborate and build relationships across teams without direct authority.
- Strong written, verbal and presentation communication skills.
Demonstrated curiosity, adaptability and commitment to continuous learning.
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What you’ll experience working for ULS
UL Solutions has been pioneering change since 1894 and we’re still leading the way. From day one, we’ve blazed a trail protecting the planet and everyone on it. Our teams have influenced billions of products, plus services, software offerings and more. We break things, burn things and blow things up. All in the name of safety science.
That’s where you come in — because none of it could happen without you. It takes passion to protect people, problem\-solving to safeguard personal data and conviction to make the world a more sustainable place. It takes bold ideas and brilliant minds to build a better world for future generations across the globe.
This is more than a job. It’s a calling. A passion to use our expertise and play our part in creating a more secure, sustainable world today — and tomorrow. As a member of our safety science community, you’ll use your ideas, your energy and your ambition to innovate, challenge and ultimately, help create a safer world.
Everyone here is unique. But we’re also a global community, working together to help create a safer world. Join UL Solutions and you can connect with the brightest minds in the business, all bringing their distinct perspectives and diverse backgrounds together to deliver real change.
Empowering our customers to keep the world safe means thinking ahead. It means investing in training and empowering our people to learn and innovate. At UL Solutions, we help build a better future — one where everyone benefits.
Join UL Solutions to be at the center of safety. To learn more about us and the work we do, visit UL.com
Total Rewards: We understand compensation is an important factor as you consider the next step in your career. The estimated salary range for this position is $120,000 to $140,000 USD and is based on multiple factors, including job\-related knowledge/skills, experience, geographical location, as well as other factors. This position is eligible for annual bonus compensation with a target payout of 20% of the base salary. This position also provides health benefits such as medical, dental and vision; wellness benefits such as mental and financial health; and retirement savings (401K) commensurate with the standard rewards offered in each individual location or country. We also provide full\-time employees with paid time off including vacation (15 days), holiday and personal days (totaling 12 days) and sick time off (72 hours).
\#LI\-SG2
\#LI\-Hybrid
A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. UL Solutions delivers testing, inspection and certification services, together with software products and advisory offerings, that support our customers’ product innovation and business growth. The UL Mark serves as a recognized symbol of trust in our customers’ products and reflects an unwavering commitment to advancing our safety mission. We help our customers innovate, launch new products and services, navigate global markets and complex supply chains, and grow sustainably and responsibly into the future. Our science is your advantage.
We may not help develop smart homes of the future, inspect the New Year’s Eve ball or work in state\-of\-the\-art labs… but we do tell people about it. It’s our brand, stories and campaigns that drive the growth of our business, open us up to new opportunities and let the world know how we’re making a difference. Our full\-service team, which includes award\-winning in\-house creatives, collaborates to share ideas, tell our story and connect with people around the world. Join our team and spread the word about an organization that’s working at the forefront of innovation to shape a safer world.
Salary Context
This $120K-$140K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At UL Solutions, 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 $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($130K) sits 40% below the category median. Disclosed range: $120K to $140K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
UL Solutions AI Hiring
UL Solutions has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Chicago, IL, US. Compensation range: $140K - $140K.
Location Context
AI roles in Chicago pay a median of $192,900 across 197 tracked positions. That's 10% below the national 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 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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