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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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João Ralha

João Ralha

Senior-level
Full Time, Contract
data science deep learning
python sql spark pytorch tensorflow +5
Open profile
Juan Sebastian Leguizamon Archila

Juan Sebastian Leguizamon Archila

Senior-level
Contract, Part Time
MLOps ai jobs
aws devops kubernetes sagemaker bedrock +4
Open profile
Gábor Vecsei

Gábor Vecsei

Executive-level
Contract, Full Time
AI & Machine Learning Engineers NLP & Prompt Engineering
python computer vision tensorflow pytorch scikit-learn +4
Open profile
Nelson Ochieng

Nelson Ochieng

Senior-level
Part Time, Freelance
AI Business, Marketing & Strategy NLP & Prompt Engineering
prompt design chatgpt rag marketing automation business intelligence +3
Open profile
Subhadeep Mandal

Subhadeep Mandal

Entry-level
Full Time
data science ml (machine learning)
pytorch fastapi langchain flask nlp +5
Open profile
Praveen Kumar

Praveen Kumar

Mid-level
Full Time, Freelance
prompt engineering computer vision
ml ai data analytics nlp llm +5
Open profile
Gamze Ozdemir

Gamze Ozdemir

Entry-level
Contract, Full Time
NLP & Prompt Engineering AI & Machine Learning Engineers
prompt design business intelligence python sql
Open profile
Danny Sebastian Diaz Padilla

Danny Sebastian Diaz Padilla

Mid-level
Full Time
ai jobs deep learning
retrieval augmented generation (rag) python machine learning deep learning mlops +5
Open profile
Wisnu Agastya

Wisnu Agastya

Mid-level
Full Time
ml (machine learning) Engineering
python go mysql postgresql elasticsearch +5
Open profile
Ayush Rahangdale

Ayush Rahangdale

Mid-level
Full Time
ml (machine learning) deep learning
python machine learning deep learning mlops sql +3
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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