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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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B

Bolajoko Simeon

Entry-level
Full Time, Part Time
MLOps & Industrialisation AI & Machine Learning Engineers
python tensorflow pytorch scikit-learn pandas +5
Open profile
J

Josmar Augusto Fonseca Barbosa

Executive-level
Contract, Full Time
prompt engineering MLOps
python c++ sql nosql openai +5
Open profile
J

Jacob Dillon

Senior-level
Full Time
NLP & Prompt Engineering AI & Machine Learning Engineers
snowflake pytorch kafka prompt design reinforcement learning +2
Open profile
Gayathri Priya Chennamareddy Gari

Gayathri Priya Chennamareddy Gari

Mid-level
Full Time, Part Time
generative ai NLP
programming python machine learning
Open profile
M

Mayur Khandekar

Mid-level
Full Time
generative ai NLP & Prompt Engineering
python generative ai aws bedrock docker
Open profile
Jack Steve

Jack Steve

Mid-level
AI & Machine Learning Engineers data science & analytics
python tensorflow computer vision reinforcement learning pandas
Open profile
A

Arnab Chakravarty

Senior-level
Full Time
AI & Machine Learning Engineers MLOps & Industrialisation
python tensorflow chatgpt langchain rag +5
Open profile
Jayant Verma

Jayant Verma

Mid-level
Full Time
MLOps ai jobs
python kubernetes docker
Open profile
K

Kriti Pawar

Senior-level
Full Time
data science NLP
ml deep learning automation llm
Open profile
H

Henrique Lucas Oliveira Evangelista

Senior-level
Full Time, Contract
MLOps ml (machine learning)
mlops python kubernetes aws terraform +1
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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