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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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Fethi

Fethi

Senior
Ethiopia — Addis Ababa (UTC+3) Full-time, Freelance
data science & analytics AI Business, Marketing & Strategy
sql power bi prompt engineering etl tableau +2
Open profile
J

Jay Dobariya

Entry-level
Full Time
Automation & AI Workflows
python pandas hugging face prompt engineering rag +5
Open profile
A

Artem

Mid-Level
Spain — Madrid (UTC+2) Full-time, Contract
Automation & AI Workflows NLP & Prompt Engineering
python openai api tensorflow numpy
Open profile
J

Jair

Junior
Mexico — Mexico City (UTC-6) Full-time
AI & Machine Learning Engineers
python prompt engineering ai agents docker openai api
Open profile
Jasia Z.

Jasia Z.

Mid-Level
Pakistan — Karachi (UTC+5) Full-time
data science & analytics NLP & Prompt Engineering
python openai api pytorch llamaindex
Open profile
Ritesh

Ritesh

Junior
India — Kolkata (UTC+5.5) Full-time, Contract
AI & Machine Learning Engineers MLOps & AI Infrastructure
python pytorch ci/cd docker openai api +5
Open profile
K

Kaarnika

Junior
India — Kolkata (UTC+5.5) Full-time
AI & Machine Learning Engineers data science & analytics
python sql snowflake tensorflow etl +5
Open profile
N

Naganathan

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Part-time
MLOps & AI Infrastructure AI & Machine Learning Engineers
kubernetes python sql aws databricks +4
Open profile
A

Alari

Senior
Estonia — Tallinn (UTC+3) Full-time, Part-time
AI & Machine Learning Engineers Automation & AI Workflows
python sql tensorflow aws scikit-learn +5
Open profile
N

Neha

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