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Mlops Data Engineer Jobs in Delaware (NOW HIRING)

... Engineer to design and develop AI and Machine Learning solutions specifically for banking ... data and deployment layers • Write efficient Python code using AI frameworks • Follow MLOps ...

Applies data extraction, transformation and loading techniques in order to connect large data sets ... Collaborate closely with the MLOps, product teams, business stakeholders, machine learning ...

Applies data extraction, transformation and loading techniques in order to connect large data sets ... Work closely with the MLOps team to create and maintain robust evaluation solutions and tools to ...

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Mlops Data Engineer information

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps engineers in demand?

MLOps Data 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 as organizations prioritize operationalizing AI solutions.

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

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps Data Engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What are MLOps Data Engineers?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What is the salary of data engineer in MLOps?

The salary of an MLOps Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning tools tend to earn higher salaries.

What engineer makes 500,000 a year?

Highly experienced senior MLOps Data Engineers with specialized skills in cloud platforms, automation, and large-scale data processing can earn salaries approaching or exceeding $500,000 annually, especially in competitive tech hubs or large organizations. Such roles often require advanced certifications, extensive experience, and expertise in tools like Kubernetes, Docker, and cloud services like AWS or Azure.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer’s ability to support scalable and reliable ML systems.
What are popular job titles related to Mlops Data Engineer jobs in Delaware? For Mlops Data Engineer jobs in Delaware, the most frequently searched job titles are:
What cities in Delaware are hiring for Mlops Data Engineer jobs? Cities in Delaware with the most Mlops Data Engineer job openings:

Data & AI Senior Engineer - 90405345 - Remote

Amtrak

Wilmington, DE • On-site, Remote

$118K - $156K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago


Amtrak rating

8.0

Company rating: 8.0 out of 10

Based on 144 frontline employees who took The Breakroom Quiz

38th of 96 rated public transport


Job description

Your success is a train ride away!

As we move America's workforce toward the future, Amtrak connects businesses and communities across the country. We employ more than 20,000 diverse, energetic professionals in a variety of career fields throughout the United States. The safety of our passengers, our employees, the public and our operating environment is our priority, and the success of our railroad is due to our employees.

Are you ready to join our team?

Our values of 'Do the Right Thing, Excel Together and Put Customers First' are at the heart of what matters most to us, and our Core Capabilities, 'Building Trust, Accountability, Effective Communication, Customer Focus, and Proactive Safety & Security' are what every employee needs to know and do to be most impactful at Amtrak. By living the Amtrak values, focusing on our capabilities, and actively embracing and fostering diverse ideas, backgrounds, and perspectives, together we will honor our past and make Amtrak a company of the future.

JOB SUMMARY:

Work Environment: Remote

The Data & AI Senior Engineer  advances Amtrak's mission to make trusted, high-quality, and intelligent data broadly accessible for decision-making, automation, and innovation. This role is responsible for leading the design and delivery of complex data and AI solutions that power Amtrak's analytics, operational systems, and digital experiences.

Senior Engineers apply deep technical expertise to architect and optimize pipelines, integrations, and data services. They ensure solutions meet performance, security, and governance standards while mentoring junior engineers and influencing design decisions across teams. The Senior Data & AI Engineer acts as both a hands-on developer and a technical leader, helping to scale Amtrak's data and AI capabilities through standardization, reusability, and continuous improvement.

ESSENTIAL FUNCTIONS:

  • Lead the design and evolution of scalable data and AI platform capabilities across Databricks (lakehouse), SAP data environments (e.g., Datasphere/S/4), and virtualization layers (e.g., Denodo) to deliver a unified, governed, self-service ecosystem.
  • Provide hands-on technical guidance in coding, API-first integrations, model lifecycle management, pipeline development, and integration patterns.
    Architect and enforce engineering standards across ingestion, transformation, feature engineering, model deployment, and governance-as-code controls embedded directly into pipelines.
  • Mentor junior and mid-level engineers, fostering skill development, collaboration, and engineering excellence.
  • Partner with architects, product owners, and governance leads to align solutions with Amtrak's enterprise data strategy and roadmap.
  • Design and implement reusable platform accelerators including APIs, templates, and feature engineering patterns that enable self-service analytics and AI across domains.

MINIMUM QUALIFICATIONS:

Education: Bachelor's degree in Computer Science, Data Engineering, or a related technical field; equivalent experience may be considered.
Experience: 4-6 years of experience in data engineering, software development, or data architecture.

PREFERRED QUALIFICATIONS:

  • Experience in a leadership capacity within a scaled agile environment or data platform modernization initiative.
  • Familiarity with enterprise data governance, metadata management, and security standards.
  • Exposure to MLOps, cloud data platforms, and automation tools that accelerate delivery.
  • Experience implementing production-grade MLOps pipelines, including model versioning, CI/CD, monitoring, and governance controls embedded into data and AI workflows.
  • Prior mentorship or technical leadership of multi-functional project teams.

REQUIRED KNOWLEDGE, SKILLS and ABILITIES:

  • Advanced proficiency in Python and SQL with deep experience in distributed data processing (e.g., Spark) and modern lakehouse architectures (Databricks strongly preferred), including integration of SAP data platforms and virtualization technologies into enterprise-scale solutions.
  • Strong understanding of data quality, observability, and performance optimization.
  • Demonstrated ability to lead teams through technical challenges while remaining hands-on in design and coding.
  • Experience working within agile product teams, coordinating across multiple stakeholders.
  • Strong understanding of API-first and event-driven architecture patterns, including secure service-to-service communication and role-based access control (RBAC).
  • Experience embedding data quality validation, schema enforcement, lineage tracking, and policy-as-code controls directly into pipelines and AI workflows.
  • Excellent communication, collaboration, and problem-solving abilities.
  • Experience building reusable cost effective, feature stores, semantic layers, or internal platform services that enable self-service analytics and AI.

The salary/hourly range is $86,500.00 - $111,996.00. Pay is based on several factors including but not limited to education, work experience, certifications, etc. Depending on an employee's assigned worksite or location, Amtrak may consider a geo-pay differential to be applied to the employee's base salary. Amtrak may offer additional incentive and pay programs to recognize and reward our employees, including a short-term incentive bonus based upon factors such as individual and company performance that is commensurate with the level of the position. In addition to your salary, Amtrak offers a comprehensive benefit package that includes health, dental, and vision plans; health savings accounts; wellness programs; flexible spending accounts; 401K retirement plan with employer match; life insurance; short and long term disability insurance; paid time off; back-up care; adoption assistance; surrogacy assistance; reimbursement of education expenses; Public Service Loan Forgiveness eligibility; Railroad Retirement sickness and retirement benefits; and rail pass privileges. Learn more about our benefits offerings here.

Requisition ID:166067

Work Arrangement:06-Onsite 4/5 Days Click here for more information about work arrangements at Amtrak.
Relocation Offered:No
Travel Requirements:Up to 25%

You power our progress through your performance.

We want your work at Amtrak to be more than a job. We want your career at Amtrak to be a fulfilling experience where you find challenging work, rewarding opportunities, respect among colleagues, and attractive compensation. Amtrak maintains a culture that values high performance and recognizes individual employee contributions.


Amtrak is committed to a safe workplace free of drugs and alcohol. All Amtrak positions requires a pre-employment background check that includes prior employment verification, a criminal history check and a pre-employment drug screen.

Candidates who test positive for marijuana will be disqualified, regardless of any state or local statute, ordinance, regulation, or other law that legalizes or decriminalizes the use or possession of marijuana, whether for medical, recreational, or other use. Amtrak's pre-employment drug testing program is administered in accordance with DOT regulations and applicable law.


In accordance with DOT regulations (49 CFR 40.25), Amtrak is required to obtain prior drug and alcohol testing records for applicants/employees intending to perform safety-sensitive duties for covered Department of Transportation positions. If an applicant/employee refuses to provide written consent for Amtrak to obtain these records, the individual will not be permitted to perform safety-sensitive functions.

In accordance with federal law governing security checks of covered individuals for providers of public transportation (Title 6 U.S.C. 1143), Amtrak is required to screen applicants for any permanent or interim disqualifying criminal offenses.


Note that any education requirement listed above may be deemed satisfied if you have an equivalent combination of education, training and experience.


Amtrak is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race/color, to include traits historically associated with race, including but not limited to, hair texture and hairstyles such as braids, locks and twists, religion, sex (including pregnancy, childbirth and related conditions, such as lactation), national origin/ethnicity, disability (intellectual, mental and physical), veteran status, marital status, ancestry, sexual orientation, gender identity and gender expression, genetic information, citizenship or any other personal characteristics protected by law.


What Amtrak employees say

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Amtrak logo

About Amtrak

Sourced by ZipRecruiter

As we move America's workforce toward the future, Amtrak connects businesses and communities across the country. We employ more than 20,000 diverse, energetic professionals in a variety of career fields throughout the United States. The safety of our passengers, our employees, the public and our operating environment is our priority, and the success of our railroad is due to our employees.

Industry

Travel arrangement services

Company size

10,000+ Employees

Headquarters location

Washington, DC, US

Year founded

1971