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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 ...

Elevance Health

Gen AI Engineer

Wilmington, DE · Hybrid

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

Elevance Health

Gen AI Engineer

Wilmington, DE · Hybrid

Work closely with the MLOps team to create and maintain robust evaluation solutions and tools to ... engineers for the deployment of machine learning models into production environments, ensuring ...

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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 Jul 31, 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.

Are MLOps engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

What is an MLOps Engineer job?

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 engineers make $300,000 a year?

Senior MLOps engineers with extensive experience, advanced skills in machine learning deployment, cloud platforms, and automation tools can earn $300,000 or more annually. High compensation is often associated with specialized expertise, leadership roles, and working in competitive tech environments.

What engineers make $500,000?

Senior-level engineers in specialized fields such as software engineering, data engineering, and MLOps engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. Compensation often includes base salary, bonuses, and stock options, particularly in high-growth tech companies.

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 in the Mlops Engineer position, 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 does an MLOps engineer do?

An MLOps engineer is responsible for deploying, managing, and maintaining machine learning models in production environments. They work with tools like Docker, Kubernetes, and cloud platforms to automate workflows, ensure model reliability, and monitor performance. Their role combines software engineering, data science, and DevOps practices to streamline the deployment and lifecycle management of machine learning systems.
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 July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $148,133 per year, or $71.2 per hour.

GenAI Engineer

Tata Consultancy Service Limited

Wilmington, DE • On-site

$100K - $110K/yr

Full-time

Re-posted 13 days ago

Job description

GenAI Engineer
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
Salary Range- $100,000-$110,000 a year
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