Celanese Engineered Materials is seeking an Engineer, Digital Innovation - Predictive Modeling & Advanced Experimentation role. This role is a specialized technical position focused on applying AI ...
Celanese Engineered Materials is seeking an Engineer, Digital Innovation - Predictive Modeling & Advanced Experimentation role. This role is a specialized technical position focused on applying AI ...
Celanese Engineered Materials is seeking an Engineer, Digital Innovation - Predictive Modeling & Advanced Experimentation role. This role is a specialized technical position focused on applying AI ...
Celanese Engineered Materials is seeking an Engineer, Digital Innovation - Predictive Modeling & Advanced Experimentation role. This role is a specialized technical position focused on applying AI ...
Senior Machine Learning Engineer - Physical AI
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Optimize models for deployment on edge and embedded targets, applying quantization, pruning, and distillation techniques to meet latency and memory constraints. * Deploy models to constrained ...
Senior Machine Learning Engineer - Physical AI
$101K - $139K/yr
Optimize models for deployment on edge and embedded targets, applying quantization, pruning, and distillation techniques to meet latency and memory constraints. * Deploy models to constrained ...
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Actimize Developer
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Data Science Manager- Credit Card Pricing & Profitability
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Data Science Manager- Credit Card Pricing & Profitability
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Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency. * Implement optimization strategies to fine-tune generative models for specific NLP ...
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The Gen AI Engineer is responsible for analyzing and modeling organizational data for the Artificial Intelligence (AI) function to draw business insights, which can be used to make business decisions.
Gen AI Engineer
Wilmington, DE · Hybrid
The Gen AI Engineer is responsible for analyzing and modeling organizational data for the Artificial Intelligence (AI) function to draw business insights, which can be used to make business decisions.
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Wilmington, DE · Hybrid
The Gen AI Engineer is responsible for analyzing and modeling organizational data for the Artificial Intelligence (AI) function to draw business insights, which can be used to make business decisions.
Gen AI Engineer
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The Gen AI Engineer is responsible for analyzing and modeling organizational data for the Artificial Intelligence (AI) function to draw business insights, which can be used to make business decisions.
Gen AI Engineer
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The Gen AI Engineer is responsible for analyzing and modeling organizational data for the Artificial Intelligence (AI) function to draw business insights, which can be used to make business decisions.
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The Gen AI Engineer is responsible for analyzing and modeling organizational data for the Artificial Intelligence (AI) function to draw business insights, which can be used to make business decisions.
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Generative AI Model Implementation: * Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks. * Integrate pre-trained models or build ...
Model information
See Delaware salary details
$16.68 is the 25th percentile. Wages below this are outliers.
$10.10 - $22.16
46% of jobs
The median wage is $24.69 / hr.
$22.16 - $34.21
20% of jobs
$34.21 - $46.26
3% of jobs
$56.59 is the 75th percentile. Wages above this are outliers.
$46.26 - $58.31
7% of jobs
$58.31 - $70.36
0% of jobs
$70.36 - $82.41
7% of jobs
$82.41 - $94.47
13% of jobs
$94.47 - $106.52
2% of jobs
$106.52 - $118.57
0% of jobs
$118.57 - $130.62
1% of jobs
$130.62 - $142.67
1% of jobs
$10
$45
$142
How much do model jobs pay per hour?
What are some common challenges faced by models during photo shoots and runway shows?
What are models?
What job makes $10,000 a month without a degree?
What is the difference between Model vs Data Analyst?
| Aspect | Model | Data Analyst |
|---|---|---|
| Required Credentials | Knowledge of statistical modeling, programming skills (e.g., Python, R) | Proficiency in data analysis tools, Excel, SQL, and visualization software |
| Work Environment | Often in tech, finance, or research settings focusing on building predictive models | In various industries analyzing data to inform business decisions |
| Employer & Industry Usage | Used in industries requiring predictive analytics and machine learning | Common across business, marketing, healthcare, and finance sectors |
The main difference is that a Model develops predictive or statistical models, while a Data Analyst interprets data to generate insights. Models focus on creating algorithms, whereas Data Analysts focus on analyzing and visualizing data to support decision-making.
How do you get hired as a model?
Is 30 too old to start modeling?
What Does a Model Do?
What are the key skills and qualifications needed to thrive as a Model, and why are they important?
Celanese rating
7.6
Based on 24 frontline employees who took The Breakroom Quiz
49th of 90 rated chemical manufacturers
Job description
Celanese Engineered Materials is seeking an Engineer, Digital Innovation - Predictive Modeling & Advanced Experimentation role. This role is a specialized technical position focused on applying AI + Physics into predictive modeling, experimental design, and Bayesian optimization to enable faster, more confident decisions in new product and material development.
This role is an opportunity to play a key role in advancing predictive modeling and advanced experimental strategy to accelerate the design and development of next-generation materials. Applying rigorous quantitative methods to enable informed decision-making early in technology and product development.
The role operates at the intersection of modeling, statistics, and machine learning, with a strong emphasis on translating these capabilities into practical approaches that support technology and innovation programs. This position also builds and deploys digital methods to guide experimentation, prediction, and optimization that support computer aided engineering and new product development efforts.
**Location can be hybrid in one of the following locations:
- Wilmington, DE
- Florence, KY
- Auburn Hills, MI
- Irving, TX
Responsibilities:
Predictive Modeling for Material Property Design
- Develop and apply predictive and hybrid machine learning approaches for the prediction of properties key to designing the next generation of materials.
- Integrate mechanistic understanding, statistical modeling, and data-driven methods to generate reliable, decision-ready predictions.
- Quantify model confidence and limitations to support risk-aware technical decisions.
- Translate complex modeling outputs into clear, actionable insights for technology and innovation stakeholders.
Experimental Design & Bayesian Optimization for New Product Development
- Design and apply advanced experimental design strategies and Bayesian optimization for new product development.
- Efficiently explore high-dimensional design spaces to prioritize experiments and identify optimal candidates for laboratory evaluation.
- Apply adaptive and sequential learning approaches to balance exploration and exploitation under limited data conditions.
Qualifications:
- Master's Degree or higher, or with equivalent experience in computer science, computer engineering, machine learning, physics, applied mathematics or related field
- Understanding of advanced materials, chemical processes, and laboratory data is a plus.
- 1+ years' work experience with modeling development, data analysis, business communication, and digital transformation is highly desirable.
- Proficiency in AI + physics-based machine learning.
- Working understanding of material science fundamentals
- Strong foundation in applied statistics, experimental design, and probabilistic modeling.
- Expertise in predictive modeling and simulation for material or system property prediction.
- Experience with uncertainty quantification, model validation, and decision support under uncertainty.
- Ability to translate advanced quantitative methods into practical workflows including proof-of-concept full-stack (backend + frontend) applications that inform technology and product decisions.
- Working across the full lifecycle: problem formulation → model and strategy development → application and adoption.
- Communicating complex modeling and experimental concepts clearly to diverse technical audiences.
- Influencing technology and innovation decisions through quantitative, model-driven insight.
- Operating effectively in cross-functional environments spanning product development, technology, innovation, and digital teams.
About Celanese
Sourced by ZipRecruiter
We produce products that make our lives a little easier, by helping customers to bring their inspired ideas and innovations to life. From the global production network of our Acetyl Chain, we provide materials that are critical to the global chemicals and paints and coatings industries. From our broad portfolio of Materials Solutions, we advance automotive and consumer electronic designs and enable life-improving medical, food and beverage products – we offer solutions to our customers to help them succeed.
Industry
Chemical manufacturing
Company size
5,001 - 10,000 Employees
Headquarters location
Irving, TX, US
Year founded
1912