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Research Scientist
The Research Scientist, reporting to Sr. Director R\&D \- Decking, Railing \& Accessories Product Development, is expected to be a recognized key and critical contributor providing technical direction for major projects in developing decking products with high levels recycled PVC resin in the formulations. The individual is a leader in the formulation and process technology needed to achieve our goals of increasing recycle content while delivering market leading products to our targeted markets. This individual will develop an in\-depth understanding of product technology and end use performance, and use this insight to deliver technical, cost reduction, and product projects for business impact and growth.
Responsibilities:
- Expand our understanding and use of PVC products and formulations that utilize greater recycle PVC resin to characterize and specify recycled PVC blends.
- Works on problems of diverse scope, including product/process development, product/process/improvement, field issue resolution, manufacturing efficiencies, and outsourcing support.
- Provides technical direction for major projects, having significant impact on sales or process efficiency. Simultaneously leads several other small projects.
- Expected to have innovative design advances for product and process development.
- Required to present technical direction for major projects and programs that impact a key product area and technology advancement.
- Required to network, internally and externally, to acquire information for projects and identify future opportunities.
- Has knowledge of the industry segment for a single product, including key drivers. Understands competitive technologies.
- Develops FFUs and translates into product specifications. Is practiced in the company's scale\-up process from experimentation to commercialization
- Develop project schedules, incorporating key tactical items for other functional areas.
- Required to present program and project proposals with justification to R\&D and other senior management.
- Integrate Lean/Six Sigma and continuous improvement in all projects
- Work with external suppliers and partners to drive projects to the correct conclusion in a timely manner.
POSITION QUALIFICATIONS:
- PhD with 0 to 5 years relevant experience
- MS with a minimum of 3 years of relevant experience
- BS with 5 years of relevant experience
- Degrees in Chemistry, Materials Science, Polymer Science and Engineering or Chemical Engineering are strongly preferred.
- Lean Six Sigma experience is desirable.
Other desired skills:
- Direct experience with formulation and extrusion of polymer systems for exterior use, preferably for building products.
- Demonstrated experience with formulation of systems encompassing process aides, weathering packages, and colorant systems
- Working knowledge of outdoor and accelerated weathering test methods, product requirements and equipment
- Familiarity with US and International Building Code requirements, particularly for exterior Residential Building products is preferred.
- Publication record showing competence with Public Speaking, Contributions to technical literature, and Intellectual Property protection via Patents and Patent Applications.
- Strong background in manufacturing systems, data collection and statistical analysis.
- Demonstrated success in interfacing with internal (manufacturing, engineering, quality) and external (contractors, vendors) customers.
- Excellent mechanical aptitude.
- Understand manufacturing processes and technologies
Skills
Candidates should be data driven decision makers.
Candidate soft skills: good multitasking, experienced working well with vendors and contractors. Analytical. Good follow\-up. Strong safety mindset. Works well with all levels of operational staff.
As of the date of this posting, a good faith estimate of the current pay scale for this position is $85,000 to $100,00\. Placement in the range depends on several factors such as experience, skills, geography and internal equity and may change over time. This position qualifies for benefits and you will be eligible to participate in a bonus plan.
At James Hardie, we recognize that our success depends on our people. We've worked hard to build a generous and competitive benefits program that demonstrates our commitment to our employees.
- Compensation: competitive salary and bonus eligibility
- Insurance: health coverage medical, dental, vision, life insurance
- Paid Time Off: vacation and company holidays
- Retirement: 401(k) with match
- Work\-Life Balance: parental leave, wellness programs
- Purpose. Impact. Community: Sustainability Initiatives \| James Hardie (https://www.jameshardie.com/all\-about\-james\-hardie/sustainability\-esg\-initiatives/)
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 3,708 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Ultralox, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills in Demand for This Role
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 197 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000.
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.
Ultralox AI Hiring
Ultralox has 1 open AI role right now. They're hiring across Research Scientist. Based in Wilmington, OH, US.
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 Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
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).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
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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