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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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Kombo Edouard

Kombo Edouard

Senior-level
Full Time, Freelance
AI & Machine Learning Engineers
python tensorflow pytorch scikit-learn reinforcement learning +5
Open profile
Chigozie Enem

Chigozie Enem

Entry-level
Full Time, Part Time
NLP & Prompt Engineering AI Business, Marketing & Strategy
chatgpt langchain rag prompt design hugging face +5
Open profile
Maowiz Saleem

Maowiz Saleem

Entry-level
Full Time, Contract
AI & Machine Learning Engineers
python tensorflow scikit-learn keras reinforcement learning +4
Open profile
Aryan Mathur

Aryan Mathur

Entry-level
Contract, Internship
AI & Machine Learning Engineers NLP & Prompt Engineering
python sql hugging face aws computer vision +5
Open profile
Vincent Koc

Vincent Koc

Executive-level
Full Time, Contract
generative ai MLOps
python prompt engineer leadership langchain autogen +1
Open profile
Kristin Meeler

Kristin Meeler

Senior-level
Full Time, Part Time
generative ai ml (machine learning)
python machine learning llm genai vectordb +5
Open profile
Suman Mondal

Suman Mondal

Entry-level
Full Time
NLP & Prompt Engineering AI & Machine Learning Engineers
rag langchain hugging face gcp python +5
Open profile
Rahul Tripathi

Rahul Tripathi

Senior-level
Full Time
ai jobs data science
generative ai python machine learning deep learning llm +4
Open profile
Doris Mugah

Doris Mugah

Mid-level
Contract, Full Time
AI & Machine Learning Engineers MLOps & Industrialisation
python tensorflow pytorch scikit-learn keras +3
Open profile
Jasur

Jasur

Mid-level
Part Time, Full Time
NLP deep learning
langchain langgraph pytorch python
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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