ZipRecruiter

Log In

1

Mlops Jobs in Raleigh, NC (NOW HIRING)

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site

Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges. • Model Deployment and MLOps: Oversee the deployment of machine ...

Redhat

Senior Data Engineer

Raleigh, NC · Remote

$103K - $140K/yr

Operationalize MLOps methodologies using MLflow for experiment tracking and model registry management, and Lakehouse monitoring for automated post-production model performance tracking to optimize ...

Red River

Senior Data Engineer

Raleigh, NC · Remote

$180K/yr

Operationalize MLOps methodologies using MLflow for experiment tracking and model registry management, and Lakehouse monitoring for automated post-production model performance tracking to optimize ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

Model Deployment and MLOps : Oversee the deployment of machine learning models into production environments, ensuring scalability and reliability. * Documentation Standards : Establish comprehensive ...

NCSU

Temporary IT Analyst / Programmer II

Raleigh, NC · On-site

$30 - $39/hr

This role involves managing multiple interns who will contribute to software development along specific pathways, including a Machine Learning Operations (MLOps) pathway. This pathway will bridge ...

previous pagenext page

Showing results 21-40

All JobsMlops JobsMlops Jobs in Raleigh, NC

Mlops information

See Raleigh, NC salary details

$98.1K

$154K

$183.2K

How much do mlops jobs pay per year?

As of Aug 15, 2026, the average yearly pay for mlops in Raleigh, NC is $153,963.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,470.00 and $167,218.00 per year, depending on experience, location, and employer.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

What are the key skills and qualifications needed to thrive as an MLOps engineer?

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What are the most commonly searched types of Mlops jobs in Raleigh, NC?

The most popular types of Mlops jobs in Raleigh, NC are:

What are popular job titles related to Mlops jobs in Raleigh, NC?

For Mlops jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Mlops jobs in Raleigh, NC look for?

The top searched job categories for Mlops jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Mlops jobs?

Cities near Raleigh, NC with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Raleigh, NC as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, and 7% Contract. Highlights an 70% Physical, 10% Hybrid, and 20% Remote job distribution, with an average salary of $153,963 per year, or $74 per hour.

Director of Product Management - AI Essentials

Hewlett Packard Enterprise Development LP

Durham, NC • Hybrid

$225K - $235K/yr

Full-time

Re-posted 5 days ago

Job description

Director of Product Management - AI EssentialsThis role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs.We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

The Director of Product Management, AI Essentials is responsible for defining and driving the strategy, development, and execution of AI-powered software solutions within the organization's broader product portfolio. This individual will lead end-to-end product initiatives, partnering closely with engineering, architecture, and go-to-market teams to deliver scalable solutions that address real customer needs. The role requires a strong understanding of modern AI technologies and their practical application, along with the ability to translate complex concepts into clear product direction. This is a high-impact opportunity to shape a rapidly growing area of the business and help bring innovative AI capabilities to market.

Responsibilities:

  • Own end to end strategy, roadmap, and delivery of HPE's enterprise AI software platform across all deployment models

  • Drive modular platform architecture spanning production inference, agent deployment, GenAI workflows, and edge AI

  • Define and execute GTM strategy targeting new buyer personas (data science, MLOps, AI platform teams)

  • Build monetization and packaging strategy across modular software offerings

  • Align cross functionally with Private Cloud, Edge, and GreenLake Platform teams

  • Deliver executive ready materials and reviews with minimal iteration

  • Provides guiding principles for and defines value proposition, customer segmentation, and business case to bring innovative and disruptive business unit products to the market (i.e. Product configuration mix, Revenue/margins, financials, market share)

  • Drives integration of the product portfolios lifecycles to business unit goals across all phases of the product portfolio and business unit lifecycle (e.g. planning, development, launch, management, exit)


Education and Experience Required:

  • Bachelor's degree or equivalent in computer science, engineering or related field of study. MBA or advanced degree in computer science or engineering preferred

  • 15+ years of work experience in product management or related field

  • 5+ years of progressive product management leadership in AI/ML, data infrastructure, and/or data science domains

  • Experience building or scaling AI/ML platforms targeting data science and MLOps personas

  • Track record of taking software products from early stage to meaningful revenue

  • Deep familiarity with inference, model serving, agent frameworks, and GPU ecosystem

  • Demonstrated daily use of AI tools in professional workflow

  • Strong preference for candidates with experience in the AI ecosystem

Knowledge and Skills:

  • AI/ML Platform Expertise: Proven experience in inference operations, model lifecycle management, agent frameworks, GPU scheduling, and the enterprise AI toolchain. Please note that this role requires demonstrated expertise in AI/ML product management.

  • Software Product Management: Experience building and scaling enterprise software platforms with clear packaging, pricing, and adoption motions. Understands SaaS and platform business models.

  • AI Native Product Leadership: Uses AI tools daily to accelerate strategy, analysis, and communication. Designs products with AI as a core capability.

  • Executive Communication and Presence: Produces decision oriented materials for senior leadership with minimal revision. Engages credibly in executive forums without extensive pre wires.

  • New Market Development: Experience reaching new buyer personas and building GTM motions into technical communities (data science, MLOps, DevOps). Understands how to land with developers and scale to enterprise buyers.

  • Broad Technical Depth: Systems level understanding across AI/ML, cloud platforms, infrastructure, and security. Sees broadly across products and GTM. Uses AI to go deeper as needed.

  • Cross Functional Leadership: Aligns engineering, GTM, and operations in a matrixed environment. Forces decisions and builds credibility quickly.

  • Commercial Acumen: Connects product decisions to revenue, pricing, and competitive positioning. Understands how to build a software monetization engine.

  • Technical SME: Understanding and knowledge of the relevant industry and ability to provide product specific technical training to the team.

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates#executive, #hybridcloud

Job:

Engineering

Job Level:

DirectorThe expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 179,500 - 358,500 in Colorado // 194,000 - 388,000 in Massachusetts // 194,000 - 412,500 in California // 170,000 - 412,500 in North Carolina & Texas
The listed salary range reflects base salary. Variable incentives may also be offered.

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

The estimated job application period closure is September 1 2026; this timeline is provided for transparency and internal planning purposes.

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual's own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

Apply