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

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Abdul Faisal Hussain

Abdul Faisal Hussain

Mid-Level
United States — New York (UTC-4) Full-time, Part-time
AI & Machine Learning Engineers data science & analytics
python sql rag aws docker +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
A

Ankit

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

Fabien

Mid-Level
Japan — Tokyo (UTC+9) Full-time, Part-time
NLP & Prompt Engineering Automation & AI Workflows
prompt engineering docker kubernetes ci/cd
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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
Open profile
Ashlee

Ashlee

Junior
South Africa — Johannesburg (UTC+2) Full-time, Contract
AI & Machine Learning Engineers MLOps & AI Infrastructure
python tensorflow scikit-learn pytorch numpy +5
Open profile
Adegbenga

Adegbenga

Mid-Level
Nigeria — Lagos (UTC+1) Full-time, Part-time
AI & Machine Learning Engineers NLP & Prompt Engineering
python sql scikit-learn pandas keras +5
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Fawad

Fawad

Junior
Pakistan — Karachi (UTC+5) Full-time, Contract
AI & Machine Learning Engineers MLOps & AI Infrastructure
python sql reinforcement learning vector databases
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Even

Even

Junior
Vietnam — Ho Chi Minh (UTC+7) Full-time
MLOps & AI Infrastructure
python pytorch computer vision kafka
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Reddaiah

Reddaiah

Junior
India — Kolkata (UTC+5.5) Full-time, Freelance
AI & Machine Learning Engineers data science & analytics
python sql pandas tensorflow
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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