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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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م

مصطفي

Junior
Egypt — Cairo (UTC+3) Full-time, Freelance
AI & Machine Learning Engineers data science & analytics
tensorflow scikit-learn openai api pytorch python +3
Open profile
Njuguna

Njuguna

Senior
Kenya — Nairobi (UTC+3) Contract-to-hire, Freelance
AI & Machine Learning Engineers NLP & Prompt Engineering
python pytorch scikit-learn tensorflow keras +5
Open profile
Dev

Dev

Senior
India — Kolkata (UTC+5.5) Full-time, Part-time
data science & analytics AI Implementation & Consulting
python pytorch scikit-learn sql computer vision +5
Open profile
Harsha Vardhan

Harsha Vardhan

Junior
India — Kolkata (UTC+5.5) Full-time
AI & Machine Learning Engineers data science & analytics
python sql scikit-learn pandas numpy +5
Open profile
Lalit

Lalit

Mid-Level
India — Kolkata (UTC+5.5) Full-time
AI & Machine Learning Engineers MLOps & AI Infrastructure
python scikit-learn keras langchain tensorflow +5
Open profile
Nayeem

Nayeem

Senior
Bangladesh — Dhaka (UTC+6) Full-time, Part-time
AI & Machine Learning Engineers AI Product & Strategy
python langchain rag ai agents
Open profile
D

Daniel

Mid-Level
Nigeria — Lagos (UTC+1) Full-time, Part-time
AI & Machine Learning Engineers data science & analytics
python sql scikit-learn pytorch keras +5
Open profile
P

Priyanshu

Junior
India — Kolkata (UTC+5.5) Freelance, Part-time
AI & Machine Learning Engineers MLOps & AI Infrastructure
python computer vision hugging face pytorch
Open profile
I

Ikram Bagban

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Freelance
AI & Machine Learning Engineers
ci/cd aws docker kubernetes rag +2
Open profile
Abiola

Abiola

Mid-Level
Ethiopia — Addis Ababa (UTC+3) Full-time, Part-time
AI & Machine Learning Engineers data science & analytics
python sql tensorflow llamaindex computer vision +2
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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