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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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J

Jahid Md Hasan

Entry-level
Full Time, Part Time
ml (machine learning) generative ai
python machine learning deep learning nlp data analysis & visualization +5
Open profile
H

Hassam Ul Haq

Senior-level
Full Time, Part Time
architecture MLOps
aws azure python docker kubernetes +1
Open profile
M

Madusha Keshan

Mid-level
Full Time
AI & Machine Learning Engineers NLP & Prompt Engineering
python tensorflow pytorch scikit-learn keras +5
Open profile
J

Jatin Chotoo

Senior-level
Full Time
data science ai jobs
python r power bi analytics ai
Open profile
A

Aadarsh Unni Wilson

Mid-level
Full Time
generative ai ai jobs
python genai/llm development fastapi langchain rag (retrieval augmented generation) +5
Open profile
K

Kofi Ahenkora Asiamah

Mid-level
Full Time
data science & analytics AI & Machine Learning Engineers
python r pandas pytorch sql +3
Open profile
Muslim Mohammed

Muslim Mohammed

Entry-level
Part Time
AI & Machine Learning Engineers AI Product & Design
python langchain
Open profile
G

Ganesh Kusalkar

Entry-level
Full Time
AI & Machine Learning Engineers
python tensorflow pytorch scikit-learn keras +5
Open profile
Jayden Macdonald

Jayden Macdonald

Mid-level
Full Time
NLP generative ai
python
Open profile
Malay Das Sharma

Malay Das Sharma

Mid-level
Full Time
generative ai prompt engineering
aws & prompt engineering
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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