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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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Medikonduru Manikanta

Medikonduru Manikanta

Junior
India — Kolkata (UTC+5.5) Full-time
Automation & AI Workflows AI & Machine Learning Engineers
python sql rag langchain ai agents +4
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Emily

Emily

Junior
United States — New York (UTC-4) Freelance, Full-time
AI & Machine Learning Engineers AI Business, Marketing & Strategy
sql tensorflow pytorch python
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Emre

Emre

Senior
Turkey — Istanbul (UTC+3) Full-time, Contract
MLOps & AI Infrastructure AI & Machine Learning Engineers
python sql numpy pytorch computer vision +5
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A

Akash

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Contract
AI & Machine Learning Engineers MLOps & AI Infrastructure
sql python ai agents openai api langchain +5
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Shubham

Shubham

Senior
India — Kolkata (UTC+5.5) Full-time, Freelance
AI & Machine Learning Engineers NLP & Prompt Engineering
tensorflow scikit-learn python keras pandas
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Babu

Babu

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Part-time
data science & analytics MLOps & AI Infrastructure
llm fine-tuning hugging face ai agents mlflow
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Nayan Jyoti

Nayan Jyoti

Mid-Level
India — Kolkata (UTC+5.5) Full-time, Freelance
AI & Machine Learning Engineers NLP & Prompt Engineering
python computer vision langchain prompt engineering pandas +1
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B

Bhuvan

Junior
India — Kolkata (UTC+5.5) Contract, Full-time
MLOps & AI Infrastructure AI & Machine Learning Engineers
python sql etl reinforcement learning
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Victor

Victor

Mid-Level
Nigeria — Lagos (UTC+1) Full-time, Part-time
Automation & AI Workflows AI & Machine Learning Engineers
rag langchain aws openai api ai agents +1
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Guillaume Vigier

Guillaume Vigier

Senior
Panama — Panama (UTC-5) Full-time
AI & Machine Learning Engineers data science & analytics
python tensorflow pytorch computer vision
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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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