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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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Allen

Allen

Senior
United States — Los Angeles (UTC-7) Full-time, Part-time
NLP & Prompt Engineering Automation & AI Workflows
tensorflow pytorch keras pandas numpy +5
Open profile
Ahmed Essam

Ahmed Essam

Junior
Egypt — Cairo (UTC+3) Freelance
data science & analytics
python sql airflow openai api
Open profile
Miguel

Miguel

Mid-Level
Kenya — Nairobi (UTC+3) Full-time, Freelance
AI & Machine Learning Engineers MLOps & AI Infrastructure
sql python numpy computer vision
Open profile
M

Meher Selmi

Mid-level
Full Time
AI & Machine Learning Engineers MLOps & Industrialisation
python aws
Open profile
J

Jacob Kingi

Mid-level
Contract, Internship
computer vision deep learning
'sql' python
Open profile
N

Nihal Bendre

Entry-level
Part Time, Full Time
computer vision MLOps
opencv python machine learning
Open profile
Rahul Baburajan

Rahul Baburajan

Mid-level
Full Time, Contract
deep learning generative ai
Open profile
Volodymyr Rudyi

Volodymyr Rudyi

Senior-level
Full Time
ml (machine learning) MLOps
Open profile
B

Bhuma Siva Sekhar Reddy

Senior-level
Full Time
data science prompt engineering
python
Open profile
N

Nejc Znidar

Senior-level
Full Time, Contract
Big Data AI Marketing
python r sql
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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