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Director of Artificial Intelligence
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Requisition ID: 16010
Location:
Portland, OR, US, 97217
Pay Type: Salary
Position type: Full\-time / Salary
COMPANY OVERVIEW
Amrize is building North America. From bridges and railways to data centers, schools, offices and homes, our solutions are inside the buildings and infrastructure that connect people and advance how we live. And we invite you to come and build with us.
As the partner of choice for professional builders, we offer advanced branded solutions from foundation to rooftop. Wherever our customers are, whatever their job, we’re ready to deliver. Our 19,000 colleagues work across 1,000 sites supported by an unparalleled distribution network. Infrastructure, commercial and residential, new build, repair and refurbishment: We’re in every construction market.
Amrize listed on the New York Stock Exchange and the SIX Swiss Exchange on June 23, 2025, following our spinoff as an independent company. Join us and build *your* ambition.
Learn more atwww.amrize.com/careers
Description:
Join the Malarkey team, innovators in roofing technology with pioneering rubberized asphalt shingles designed for superior durability and sustainability. At Malarkey, we take pride in our most important asset \- our employees.
We’re seeking a Director of Artificial Intelligence who's ready to be part of our mission to manufacture and deliver innovative, performance\-driven building products with unmatched service and integrity. Our focus is creating longer\-lasting, environmentally responsible roofing solutions that can withstand all weather conditions.
Job Title: Director of Artificial Intelligence\| Req ID: 16010 \| HR Contact: Elizabeth Bertapelle\| Location: Building Envelope \- Corp Portland, OR
ABOUT THE ROLE
The Director of Artificial Intelligence (AI) is a senior enterprise leader responsible for applying AI and advanced analytics to materially improve business performance across manufacturing operations and enterprise support functions. This role is focused on practical, value\-driven AI applications. This role leverages AI to enhance quality, reliability, maintenance, forecasting, production efficiency, financial planning, workforce planning inputs, supply chain performance, and select customer or market insights. The role operates with strong governance and cross\-functional alignment, ensuring AI solutions support leadership decision\-making rather than replace it, while protecting safety, compliance, data integrity, and employee trust.
WHAT YOU’LL ACCOMPLISH
- Define and execute the business unit AI strategy to align priorities with clear success metrics, ROI expectations, and delivery timeliness.
- Identify and deliver high\-value AI use cases with measurable impact in manufacturing, quality, finance, supply chain, and workforce planning inputs.
- Deploy AI solutions supporting asset reliability, process optimization, defect prevention, and production planning.
- Align AI recommendations with operational constraints, quality standards, and safety requirements while ensuring A outputs are actionable and integrated into daily plant and leadership workflows.
- Partners with support functions on decision support, such as Finance to improve forecasting accuracy and cost visibility; HR and EHS to support workforce planning insights and leading safety indicators; Supply Chain and Marketing to enhance demand planning, inventory optimization, and customer insights.
- Establish business unit standards for AI governance, model validation, monitoring, and auditability.
- Demonstrate a commitment to communicating, improving, and adhering to health, safety, and environmental policies in all work environments and areas. Promote a culture of safety and exhibit these behaviors.
WHAT WE’RE LOOKING FOR
Education: Bachelor’s degree
Field of Study Preferred: Computer science, Data Science, Engineering, Operations Research, Industrial Engineering, Applied Mathematics
Additional Education: A master’s degree in Artificial Intelligence, Data Science, Analytics, Engineering, Business Analytics, or an MBA with a strong analytics focus is preferred.
Required Work Experience: Five or more years in a senior leadership role driving advanced analytics initiatives aligned with business strategy
Travel Requirements: 10\-20%
Additional Requirements:* Successful candidates must adhere to all safety protocols and proper use of Amrize\-approved Personal Protection Equipment (PPE), including but not limited to respirators. Employees who are required to wear respirators must be clean\-shaven where the respirator seal meets the face in order to pass the qualitative and quantitative fit tests.
WHAT WE OFFER
- Competitive salary: $170,000\-$220,000
- Retirement Savings: Choose from 401(k) pre\-tax and/or Roth after\-tax savings
- Employee Stock Purchase Plan
- Medical, Dental, Disability, and Life Insurance
- Holistic Health \& Well\-being programs
- Flexible Spending Accounts (FSAs) for health and dependent care
- Vision and other Voluntary benefits and discounts
- Paid time off \& paid holidays
- Paid Parental Leave (maternity \& paternity)
\#MALARKEY
Amrize is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
*We thank all applicants for their interest; however, only those selected for an interview will be contacted.*
BUILDING INCLUSIVE WORKSPACES
At Amrize, there is endless opportunity for you to play your part. Whether you’re in a technical, managerial, or frontline role, you can shape a career that works for you. We're seeking builders, creative thinkers and innovators. Come put your expertise to work while developing the knowledge and skills to drive your career forward. With us you’ll have the chance to build your ambition!
Amrize North America Inc. takes pride in our hiring processes and our commitment that all qualified applicants will receive consideration for employment without regard to age, race, color, ethnicity, religion, creed, national origin, ancestry, gender, gender identity, gender expression, sex, sexual orientation, marital status, pregnancy, parental status, genetic information, citizenship, physical or mental disability, past, current, or prospective service in the uniformed services, or any other characteristic protected by applicable federal, state or local law. Amrize North America Inc, and its respective subsidiaries are Equal Opportunity Employers, deciding all employment on the basis of qualification, merit and business need. Amrize Canada Inc. is committed to the principles of employment equity and encourages the applications from women, visible minorities, and persons with disabilities. Amrize North America Inc. participates in E\-Verify and will provide the federal government with your I\-9 information to confirm that you are authorized to work in the United States.
In compliance with the ADA Amendments Act (ADAAA), if you have a disability and would like to request accommodation in order to apply for a position with us, please email recruiting\[email protected]. This email address should only be used for accommodations and not general inquiries or resume submittals. In Ontario, our organization/business is committed to fulfilling our requirements under the Accessibility for Ontarians with Disabilities Act. Under the Act, accommodations are available on request for candidates taking part in all aspects of the selection process.
While we sincerely appreciate all applications, only candidates selected for an interview will be contacted.
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The only way to apply for a position at Amrize is through our official Careers website. Be cautious of unsolicited offers or requests for information from other sources. Learn how to protect yourself from recruitment fraud here: Fraudulent Job Offers Policy
Nearest Major Market: Portland Oregon
Salary Context
This $170K-$220K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Amrize, 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 $181,170 based on 12,692 positions with disclosed compensation. Director-level AI roles across all categories have a median of $247,800. This role's midpoint ($195K) sits 8% above the category median. Disclosed range: $170K to $220K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Amrize AI Hiring
Amrize has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Portland, OR, US. Compensation range: $220K - $220K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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