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Teddy

Teddy

Senior
Paris, France (UTC+1) Contract, Freelance Rate on request
MLOps ML (Machine Learning)
python docker pyspark kubernetes aws +5
Message
Uriel

Uriel

Senior
Toronto, Canada (UTC-5) Full Time, Part Time Rate on request
AI & Machine Learning Engineers NLP & Prompt Engineering
python tensorflow pytorch langchain docker +4
Message
Jahir

Jahir

Mid-Level
Kolkata, India (UTC+5:30) Full-time, Part-time Rate on request
AI & Machine Learning Engineers NLP & Prompt Engineering
python reinforcement learning hugging face numpy pandas +5
Message
Jack

Jack

Senior
Dublin, Ireland (UTC+0) Full-time Rate on request
AI & Machine Learning Engineers
python tensorflow llamaindex langchain rag +1
Message
Andrew

Andrew

Senior
Istanbul, Turkey (UTC+3) Full-time, Contract Rate on request
MLOps & AI Infrastructure AI & Machine Learning Engineers
python docker kubernetes airflow mlflow +2
Message
Abhishek

Abhishek

Senior
Kolkata, India (UTC+5:30) Full-time, Freelance Rate on request
Data Science & Analytics AI Business, Marketing & Strategy
scikit-learn python pytorch tensorflow numpy +4
Message
Moises

Moises

Senior
Bogota, Colombia (UTC-5) Part-time, Freelance Rate on request
MLOps & AI Infrastructure AI & Machine Learning Engineers
kubernetes aws python docker ci/cd +5
Message
Kevin Wang

Kevin Wang

Senior
Chicago, United States (UTC-6) Full-time Rate on request
AI & Machine Learning Engineers
python pytorch tensorflow langchain llamaindex +5
Message
Juan Sebastian Leguizamon Archila

Juan Sebastian Leguizamon Archila

Senior-level
Contract, Part Time Rate on request
MLOps AI Jobs
aws devops kubernetes sagemaker bedrock +4
Message
Sahil Arya

Sahil Arya

Senior-level
Contract, Full Time Rate on request
MLOps & Industrialisation MLOps & AI Infrastructure
python tensorflow pytorch chatgpt aws +5
Message

Hiring guide: MLOps & AI Infrastructure

Add an MLOps engineer to your team: model deployment, Kubernetes, pipeline orchestration, and production observability. New profiles are reviewed by our team. Direct contact, no agency.

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.

Profiles for critical AI systems

MLOps profiles on RemoteAI describe experience building 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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