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Add an MLOps engineer to your team — model deployment, Kubernetes, pipeline orchestration, and production observability. Every profile is manually reviewed. Direct contact, no agency.

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AI & ML Engineering Data Science & Analytics NLP & Prompt Engineering MLOps & AI Infrastructure Automation & AI Workflows

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Christine

Christine

Mid-Level
Kenya — Nairobi (UTC+3) Full-time, Freelance
Automation & AI Workflows AI Implementation & Consulting
python docker openai api sql
Open profile
M

Mitushi

Junior
India — Kolkata (UTC+5.5) Part-time, Full-time
AI & Machine Learning Engineers data science & analytics
python scikit-learn pytorch numpy
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Zoya

Zoya

Mid-Level
India — Kolkata (UTC+5.5) Contract, Freelance
AI & Machine Learning Engineers AI Product & Strategy
python rag prompt engineering llamaindex hugging face +1
Open profile
A

Ankit

Junior
India — Kolkata (UTC+5.5) Full-time
Automation & AI Workflows MLOps & AI Infrastructure
python sql mlflow ci/cd
Open profile
Emily

Emily

Junior
United States — New York (UTC-4) Freelance, Full-time
AI & Machine Learning Engineers AI Business, Marketing & Strategy
sql tensorflow pytorch python
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S

Satoshi

Mid-Level
Japan — Tokyo (UTC+9) Full-time
AI Business, Marketing & Strategy AI Implementation & Consulting
python pandas r langchain prompt engineering +3
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R

Roicy Vinu

Junior
India — Kolkata (UTC+5.5) Full-time
AI & Machine Learning Engineers NLP & Prompt Engineering
python sql rag langchain
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Rodney

Rodney

Senior
United States — Chicago (UTC-5) Full-time, Part-time
AI Product & Strategy AI & Machine Learning Engineers
python langchain kubernetes ci/cd aws +5
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Asma Kh

Asma Kh

Junior
Algeria — Algiers (UTC+1) Part-time
MLOps & AI Infrastructure
python pytorch pandas sql
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Sushumna

Sushumna

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Part-time
AI & Machine Learning Engineers data science & analytics
python numpy pandas langchain spark +5
Open profile

Category guide

Find Vetted MLOps Engineers for Your Team

Why hire MLOps & AI Infrastructure experts?

In the era of generative AI, owning a model is no longer enough. The real challenge is deployment, monitoring, reliability, and scale. MLOps and AI infrastructure specialists bring the engineering discipline needed to run production AI systems with Kubernetes, CI/CD pipelines, model versioning, observability, and better GPU cost control.

Verified profiles for critical AI systems

Each MLOps profile on RemoteAI is selected for the ability to build stable, observable, and production-ready platforms. Whether your stack depends on AWS, SageMaker, MLflow, or internal tooling, these professionals help make AI systems dependable over time. If you also want to improve the model experience itself, browse our NLP & Prompt Engineering experts.

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