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Remote Mlops Jobs in Kentucky (NOW HIRING)

Remote Mlops information

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 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.

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 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 most commonly searched types of Mlops jobs in Kentucky?

The most popular types of Mlops jobs in Kentucky are:

What are popular job titles related to Remote Mlops jobs in Kentucky?

For Remote Mlops jobs in Kentucky, the most frequently searched job titles are:

LLM Engineer (Remote)

Louisville, KY • On-site, Remote


Cognizant Technology Solutions

7.0

Company rating: 7.0 out of 10

Based on 87 frontline employees who took The Breakroom Quiz

59th of 72 rated business consultants

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Respectful managers


$141K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Job description

LLM Engineer
About the role
As LLM Engineer, you will make an impact by designing, building, optimizing, and deploying Large Language Model (LLM) and Small Language Model (SLM) solutions that power the enterprise Agent Factory. You will be a valued member of the AI Engineering team and work collaboratively with data scientists, platform engineers, product teams, and business stakeholders to deliver scalable, production-ready generative AI capabilities.
In this role, you will:
  • Design, build, fine-tune, deploy, and optimize LLM and SLM solutions for enterprise-scale use cases.
  • Develop and maintain supervised fine-tuning, model adaptation, and evaluation pipelines.
  • Apply advanced model optimization techniques including LoRA, QLoRA, distillation, quantization, and model compression to improve performance and efficiency.
  • Assess commercial, open-source, and internally hosted foundation models based on quality, cost, scalability, and operational requirements.
  • Collaborate with cross-functional teams to support domain-specific AI solutions using approved enterprise datasets and best practices for responsible AI.

Work model:
We strive to provide flexibility wherever possible. Based on this role's business requirements, this is a remote position open to qualified applicants in Louisville, KY. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
*Please note that this position is not eligible for visa transfer or sponsorship now or at any time in the future*
What you need to have to be considered
  • 7+ years of experience in Software Engineering, AI Engineering, Machine Learning Engineering, Platform Engineering, or a related technical discipline.
  • 2+ years of hands-on experience developing and deploying Generative AI, LLM, SLM, or Agentic AI solutions in production environments.
  • Experience building enterprise-grade AI applications utilizing LLMs, Retrieval-Augmented Generation (RAG), prompt engineering, APIs, and cloud or on-premises platforms.
  • Strong understanding of model fine-tuning, adaptation, evaluation frameworks, and AI quality measurement methodologies.
  • Proficiency in machine learning development, model deployment, and MLOps best practices.
  • Experience working with Python and modern AI/ML frameworks and tools.

These will help you stand out
  • Knowledge of AI infrastructure, GPU optimization, and large-scale model serving.
  • Experience implementing model governance, responsible AI, and evaluation frameworks.
  • Familiarity with vector databases, embedding models, and advanced RAG architectures.
  • Experience building enterprise AI platforms, multi-agent systems, or agent orchestration frameworks.

Salary and Other Compensation:
Applications will be accepted until September 17th, 2026.
The annual salary for this position is between $ 81,337 to $141,500 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

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