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Remote Mlops Jobs in Raleigh, NC (NOW HIRING)

Berriehill Research

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback ... This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

... remote locations. ** About our Team : LexisNexis Legal & Professional, serving customers in over ... Model Deployment and MLOps : Oversee the deployment of machine learning models into production ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

... remote locations. ** About our Team : LexisNexis Legal & Professional, serving customers in over ... Model Deployment and MLOps : Oversee the deployment of machine learning models into production ...

All JobsMlops JobsRemote Mlops JobsRemote Mlops Jobs in Raleigh, NC

Remote Mlops information

What is the difference between Remote Mlops vs Data Engineer?

AspectRemote MlopsData Engineer
Required CredentialsCertifications in cloud platforms, ML frameworks, scripting skillsDatabase, ETL, SQL, cloud certifications
Work EnvironmentRemote, cloud-based, collaboration with ML teamsRemote or on-site, data infrastructure focus
Industry UsageAI/ML companies, tech firms, startupsData-driven companies, finance, healthcare, tech
Common Search/ComparisonYesYes

Remote Mlops and Data Engineers share overlapping skills like cloud computing and scripting, but Remote Mlops focuses on deploying and maintaining ML models in production, while Data Engineers build and manage data pipelines. Both roles are essential in data-driven organizations, often collaborating but with distinct technical focuses.

What are the key skills and qualifications needed to thrive as a remote mlops engineer?

To thrive as a Remote MLOps Engineer, you need a strong background in machine learning, software engineering, and cloud computing, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and experience with ML frameworks such as TensorFlow or PyTorch are crucial, along with relevant certifications. Excellent communication, problem-solving abilities, and self-motivation are essential soft skills for collaborating across distributed teams and handling complex deployments. These skills ensure the seamless integration, deployment, and monitoring of machine learning models in production environments, driving efficiency and reliability in remote settings.

Is remote MLOps in high demand?

Remote MLOps roles are in high demand due to the increasing adoption of machine learning and AI across industries. Employers seek professionals skilled in cloud platforms, automation, and tools like Docker and Kubernetes to manage and deploy ML models efficiently in remote environments.

What is a remote mlops?

A Remote MLOps job involves managing and automating the deployment, monitoring, and maintenance of machine learning models in production environments, all while working from a remote location. MLOps stands for Machine Learning Operations, and professionals in this role bridge the gap between data science and IT operations to ensure smooth, reliable model performance. Remote MLOps engineers use tools and practices to streamline machine learning workflows, collaborate with distributed teams, and maintain infrastructure without being tied to a physical office.

What are some common challenges faced by remote mlops engineers, and how can they be overcome?

Remote MLOps engineers often face challenges related to collaborating across distributed teams, ensuring robust CI/CD pipelines for machine learning models, and maintaining secure, scalable cloud infrastructure. Effective communication using collaboration tools and thorough documentation is key to overcoming team coordination issues. Additionally, leveraging cloud-based MLOps platforms and automating routine processes can help streamline workflows and reduce operational friction, allowing engineers to focus on innovation and model optimization.
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 Remote Mlops jobs in Raleigh, NC? For Remote Mlops jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Remote Mlops jobs in Raleigh, NC look for? The top searched job categories for Remote Mlops jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Remote Mlops jobs? Cities near Raleigh, NC with the most Remote Mlops job openings:
Remote Mlops jobs near you
Infographic showing various Remote Mlops job openings in Raleigh, NC as of August 2026, with employment types broken down into 62% Full Time, and 38% Contract. Highlights an 100% Remote job distribution.

Senior MLOps Engineer- Remote[Candidates must work PST hours]

OMG Technologies

Raleigh, NC • Remote

$70/hr

Contractor

Posted 16 days ago

Job description

This opportunity is for aSenior MLOps Engineerrole with one of our clients. Please find the job description below.


Position Overview :

Role: Sr MLOps Engineer
Location:Remote[Candidates must work PST hours]
Duration:12+Months
ContractRole
Rate: $60/hr on W2 | $70/hr on C2C


Job Summary

The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with crossfunctional partners-including biostatisticians, bioinformatics scientists, AI scientists, and software engineers-to deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications.The role designs, builds, and maintains robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecycle-from data ingestion, model training, versioning and evaluation, through deployment, monitoring, and continuous improvement. This role serves as a key resource, applying indepth practical knowledge of ML Operations, software engineering, and cloud infrastructure to solve complex problems across multiple projects, ensuring AI/ML models are production-ready, observable,and aligned with the company's mission to help eradicate cancer.

Essential Duties

Include, but are not limited to, the following:

  • Designs, implements, and maintains endtoend MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
  • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and realtime inference workloads.
  • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
  • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
  • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
  • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into productiongrade services integrated into customerfacing and internal applications.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Support and comply with the company's Quality Management System policies and procedures.
  • Maintain regular and reliable attendance.
  • Ability to act with an inclusion mindset and model these behaviors for the organization.
  • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications

  • Bachelor's Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience.; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience.
  • 5 years of relevant job-related experience.
  • Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikitlearn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads.
  • Demonstrated ability to perform the essential duties of the position with or without accommodation.
  • Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time.

Preferred Qualifications

  • 2+ years of life sciences industry experience working with biological data.
  • 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
  • Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
  • Scientific understanding of cancer biology
  • Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment.

Other Job Details

  • Number of Openings:2-3
  • Work Schedule:Must be available to work PST hours
  • Industry Experience:Not required; strong technical expertise is the primary focus
  • Interviews:Video interviews.
  • Docs required:ID proof will be required

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