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Mlops Engineer Jobs in Delaware (NOW HIRING)

ClifyX

GenAI Engineer

Wilmington, DE · On-site

... Engineer to design and develop AI and Machine Learning solutions specifically for banking ... Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment) • Compliance: Banking regulations (SR 11 ...

DijavAI

AI Application Engineer

Dover, DE · On-site

$120 - $180/hr

Understanding of MLOps practices * Strong software engineering fundamentals * Experience with containerization and deployment #J-18808-Ljbffr

JPMorgan Chase & Co.

Lead Software Engineer

Wilmington, DE · On-site

$145K - $185K/yr

As a Lead Software Engineer at JPMorgan Chase within Corporate - AIML Data Platforms team , you ... Experience with MLOps frameworks and tools such as Kubeflow, MLflow, or similar AI/ML lifecycle ...

JP Morgan Chase

Lead Software Engineer

Wilmington, DE · On-site

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, you are an integral ... Experience in MLOps and building model serving applications * Experience with artificial ...

J.P. Morgan

Lead Software Engineer

Wilmington, DE · On-site

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, you are an integral ... Experience in MLOps and building model serving applications * Experience with artificial ...

Aumni

Applied AI/ML - Vice President

Wilmington, DE · On-site

$120 - $160/hr

Architect and implement robust, cloud-native MLOps/LLMOps pipelines and distributed AI/ML ... Proficiency in programming languages like Python for model development, experimentation, and ...

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All JobsMlops Engineer JobsMlops Engineer Jobs in Delaware

Mlops Engineer information

See Delaware salary details

$94.4K

$148.1K

$171.9K

How much do mlops engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for mlops engineer in Delaware is $148,133.00, according to ZipRecruiter salary data. Most workers in this role earn between $142,285.00 and $159,660.00 per year, depending on experience, location, and employer.

What is an MLOps engineer?

An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and operations by automating workflows, optimizing infrastructure, and ensuring model reliability. Their role includes CI/CD for ML models, data pipeline management, and performance monitoring. They also work with cloud platforms, containerization, and orchestration tools to scale ML systems efficiently.

What are some common challenges MLOps engineers face in their daily work?

Mlops Engineers often encounter challenges in integrating new machine learning models into existing production systems while ensuring minimal downtime and maintaining data integrity. Managing the scaling and orchestration of models across various cloud or on-prem environments can be complex, requiring close coordination with data scientists and DevOps teams. Staying up to date with rapidly evolving tools and best practices is also essential in this field. Addressing these challenges provides valuable opportunities to innovate and improve both technical processes and team collaboration.

What are the key skills and qualifications needed to thrive as an MLOps engineer, and why are they important?

To thrive as an Mlops Engineer, you need strong skills in software engineering, machine learning pipelines, and cloud infrastructure, often backed by a degree in computer science, engineering, or a related field. Familiarity with tools such as Docker, Kubernetes, TensorFlow, AWS/GCP/Azure, and CI/CD systems is essential, and certifications like AWS Certified Machine Learning or Kubernetes Administrator are often valued. Effective communication, problem-solving, and teamwork are crucial soft skills for collaborating across data science and IT teams. These abilities enable Mlops Engineers to efficiently deploy, manage, and scale machine learning models in dynamic production environments.

What do you need to be a MLOps engineer?

To become a MLOps engineer, you typically need a strong background in software engineering, machine learning, and cloud platforms. Proficiency in programming languages like Python, experience with containerization tools such as Docker, and knowledge of CI/CD pipelines are essential. Certifications in cloud services and familiarity with tools like Kubernetes and ML frameworks also enhance qualifications.

Who earns more, ML engineer or MLOps engineer?

MLOps engineers typically earn slightly more than ML engineers due to their focus on deploying, maintaining, and scaling machine learning systems, which requires expertise in cloud platforms, automation, and infrastructure. Salary differences can vary based on experience, location, and company size, but MLOps roles often command higher compensation because of their specialized skill set.

What are the most commonly searched types of Mlops Engineer jobs in Delaware?

The most popular types of Mlops Engineer jobs in Delaware are:

What are popular job titles related to Mlops Engineer jobs in Delaware?

For Mlops Engineer jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Mlops Engineer jobs in Delaware look for?

The top searched job categories for Mlops Engineer jobs in Delaware are:

Mlops Engineer jobs near you
Infographic showing various Mlops Engineer job openings in Delaware as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $148,133 per year, or $71.2 per hour.

GenAI Engineer

ClifyX

Wilmington, DE • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
ClifyX is a company focused on innovative technology solutions, and they are seeking a GenAI Engineer to design and develop AI and Machine Learning solutions specifically for banking applications. The role involves building and deploying models, ensuring compliance, and collaborating with various teams to enhance AI capabilities.
Responsibilities:
• Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.
• Build, fine-tune, and deploy ML models and LLMs for credit scoring, AML, and automation
• Implement RAG-based GenAI applications using internal banking data
• Develop scalable data pipelines for training, validation, and real-time inference
• Collaborate with risk, compliance, finance, and business teams for AI solutions
• Ensure regulatory compliance and AI governance standards
• Implement data security, privacy, and access control mechanisms
• Integrate AI models into production using APIs and microservices
• Apply prompt engineering and model optimization techniques
• Monitor model performance, drift detection, and continuous improvement
• Develop explainable AI (XAI) for transparent decision-making
• Optimize cost, latency, and scalability of AI systems
• Troubleshoot AI/ML system issues across data and deployment layers
• Write efficient Python code using AI frameworks
• Follow MLOps best practices (CI/CD, automated deployment)
• Ensure responsible AI practices (bias, fairness, ethics)
• Mentor teams and contribute to enterprise AI platforms.
Qualifications:
Required:
• Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.
• Build, fine-tune, and deploy ML models and LLMs for credit scoring, AML, and automation
• Implement RAG-based GenAI applications using internal banking data
• Develop scalable data pipelines for training, validation, and real-time inference
• Collaborate with risk, compliance, finance, and business teams for AI solutions
• Ensure regulatory compliance and AI governance standards
• Implement data security, privacy, and access control mechanisms
• Integrate AI models into production using APIs and microservices
• Apply prompt engineering and model optimization techniques
• Monitor model performance, drift detection, and continuous improvement
• Develop explainable AI (XAI) for transparent decision-making
• Optimize cost, latency, and scalability of AI systems
• Troubleshoot AI/ML system issues across data and deployment layers
• Write efficient Python code using AI frameworks
• Follow MLOps best practices (CI/CD, automated deployment)
• Ensure responsible AI practices (bias, fairness, ethics)
• Mentor teams and contribute to enterprise AI platforms.
• Languages: Python
• AI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning
• Frameworks: TensorFlow, PyTorch
• GenAI Tools: LangChain, LlamaIndex
• Vector DB: Pinecone, FAISS
• Cloud Technologies: AWS / Azure / GCP
• Data Pipelines: ETL/ELT, Real-time & Batch Processing
• Integration: APIs, Microservices
• Concepts: RAG Architecture, XAI, Model Optimization
• Methodologies: Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment)
• Compliance: Banking regulations (SR 11-7, GDPR), Model Risk Management
• Soft Skills: Strong communication, stakeholder management, and analytical thinking
Company:
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations. Founded in 1998, the company is headquartered in South Plainfield, USA, with a team of 501-1000 employees. The company is currently Late Stage.
ClifyX logo

About ClifyX

Sourced by ZipRecruiter

ClifyX is a well-established player in the IT Services sector that specializes in providing result-oriented technological solutions to a wide range of industrial verticals. Based in South Plainfield, New Jersey, ClifyX offers a comprehensive selection of IT services that include project staffing, application development, professional consulting, and other IT-based solutions. While the company's website, clifyx.com, does not divulge the exact founding date, it is clear that ClifyX has grown into a renowned name within their domain, thanks to their unwavering commitment to innovative practices. The company's mission statement revolves around harnessing the power of technology to assist their clientele in steering their respective businesses towards success.

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

South Plainfield, NJ, US

Year founded

1998

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