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Senior Machine Learning Engineer Jobs in Delaware

Celanese

Digital Innovation Engineer

Wilmington, DE · On-site

Celanese Engineered Materials is seeking an Engineer, Digital Innovation - Predictive Modeling ... Develop and apply predictive and hybrid machine learning approaches for the prediction of ...

Elevance Health

Gen AI Engineer

Wilmington, DE · Hybrid

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning engineers, and software engineers for the deployment of machine learning models into production environments ...

Diverse Lynx

AI/ML Software Engineer

Wilmington, DE · On-site

Diverse Lynx is seeking an experienced AI/ML Software Engineer to design, develop, and deploy scalable AI and Machine Learning solutions. The role involves collaborating with product managers, data ...

Berkley

Principal Engineer - AI Platform

Wilmington, DE

$131K - $175K/yr

Design and develop scalable AI platforms to support various machine learning and deep learning ... Strong knowledge of programming languages such as Python, R, and/or Java. * Experience with cloud ...

Berkley

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Design and develop scalable AI platforms to support various machine learning and deep learning ... Strong knowledge of programming languages such as Python, R, and/or Java. * Experience with cloud ...

Berkley

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Design and develop scalable AI platforms to support various machine learning and deep learning ... Strong knowledge of programming languages such as Python, R, and/or Java. * Experience with cloud ...

Diverse Lynx

AI ML Software Engineer

Wilmington, DE · On-site

... machine learning models in production. • Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API. • Experience with machine ...

Athena LLC

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Solid understanding of machine learning fundamentals and algorithms (classification, NLP, Deep ...

Athenago

AI Engineering Intern

Wilmington, DE

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Solid understanding of machine learning fundamentals and algorithms (classification, NLP, Deep ...

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All JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Delaware

Senior Machine Learning Engineer information

See Delaware salary details

$59.6K

$126.7K

$183.7K

How much do senior machine learning engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for senior machine learning engineer in Delaware is $126,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $143,600.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Delaware? The most popular types of Machine Learning Engineer jobs in Delaware are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Delaware? For Senior Machine Learning Engineer jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Delaware look for? The top searched job categories for Senior Machine Learning Engineer jobs in Delaware are:
What cities in Delaware are hiring for Senior Machine Learning Engineer jobs? Cities in Delaware with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you

Digital Innovation Engineer

Celanese International Corporation

Wilmington, DE • Hybrid

Full-time

Posted 6 days ago

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 nextgeneration materials. Applying rigorous quantitative methods to enable informed decisionmaking 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

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 datadriven methods to generate reliable, decisionready predictions.
  • Quantify model confidence and limitations to support riskaware 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 highdimensional 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.

  • 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, modeldriven insight.
  • Operating effectively in crossfunctional environments spanning product development, technology, innovation, and digital teams.

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