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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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Bandile Malaza

Bandile Malaza

Mid-level
Full Time
data science ml (machine learning)
python javascript fastapi machine learning responsible ai +4
Open profile
Vijay Ingle

Vijay Ingle

Mid-level
Full Time
Engineering AI & Machine Learning Engineers
aws docker kubernetes terraform ci/cd pipelines +3
Open profile
Saranya Omprakash

Saranya Omprakash

Mid-level
Full Time
ai jobs data science
python sql machine learning cnn ann +5
Open profile
Thomas

Thomas

Junior
Thailand — Bangkok (UTC+7) Full-time, Part-time
Automation & AI Workflows AI Implementation & Consulting
ai agents openai api python rag sql +1
Open profile
B

Babar Saeed

Junior
Pakistan — Karachi (UTC+5) Full-time
AI & Machine Learning Engineers
python pandas sql numpy
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Vidya

Vidya

Junior
India — Kolkata (UTC+5.5) Part-time, Contract
AI & Machine Learning Engineers NLP & Prompt Engineering
python sql scikit-learn tensorflow langchain +2
Open profile
Mccallum

Mccallum

Mid-Level
United States — Chicago (UTC-5) Part-time, Freelance
Automation & AI Workflows AI & Machine Learning Engineers
fastapi python openai api ai agents prompt engineering +1
Open profile
Y

Yousif

Senior
United Arab Emirates — Dubai (UTC+4) Full-time, Part-time
AI & Machine Learning Engineers MLOps & AI Infrastructure
python pytorch langchain rag sql +5
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Lilian

Lilian

Junior
France — Paris (UTC+2) Full-time, Freelance
AI & Machine Learning Engineers Automation & AI Workflows
python computer vision reinforcement learning aws llm fine-tuning +5
Open profile
Orçun

Orçun

Senior
Turkey — Istanbul (UTC+3) Full-time, Part-time
Automation & AI Workflows MLOps & AI Infrastructure
python langchain ci/cd kubernetes docker +4
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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