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CY iT HR
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Elizabeth Interexy
Elizabeth Interexy
2026-09-23 13:51 UTC
๐ฅ Hiring: Middle ML / MLOps Engineer
We are looking for an experienced Middle ML / MLOps Engineer (3+ years of experience) to join an international project! In this role, you will design, build, and deploy production-scale machine learning and Generative AI / LLM-based applications in a cloud-native environment.
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๐ Workload: Full-time (100% Remote)
๐ฃ Language: English (Fluent โ daily technical communication)
๐ป Tech Stack: Python, AWS (SageMaker), Docker, Kubernetes, PySpark, FastAPI/Flask, MLOps (MLflow / Kubeflow), LLMs
๐ Location: Remote within EU (must hold EU Citizenship, PR, or a valid EU Work/Residence Permit)
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๐ฏ Key Responsibilities:
* Design, develop, and deploy production-grade ML and LLM-based applications.
* Build and maintain robust MLOps platforms and CI/CD pipelines for machine learning workflows.
* Automate model training, evaluation, deployment, monitoring, and continuous improvement.
* Develop cloud-native ML infrastructure using AWS, SageMaker, Docker, and Kubernetes.
* Build reliable backend APIs and microservices using FastAPI or Flask.
* Collaborate closely with product, software engineering, and data teams.
---
๐ Requirements:
* 3+ years of commercial experience as an ML Engineer, MLOps Engineer, or in a related field.
* Strong hands-on experience with Python and developing production-ready services with FastAPI / Flask.
* Proven experience with AWS (specifically Amazon SageMaker).
* Hands-on experience with Docker and Kubernetes for deployment and orchestration.
* Solid understanding of MLOps practices and ML lifecycle tools (MLflow, Kubeflow, or SageMaker Pipelines).
* Practical experience working with LLMs / Generative AI in production environments.
* Hands-on experience with PySpark / Apache Spark.
* Fluent English (B2+/C1) for effective collaboration with cross-functional teams.
โญ๏ธ Nice to Have:
* Experience with recommendation systems, NLP, or forecasting use cases.
* Knowledge of model monitoring and observability tools.
---
๐ฉ To Apply:
Send your CV and expected hourly rate to @elizabeth_interexy
#vacancy #AI #MLEngineer #ML
We are looking for an experienced Middle ML / MLOps Engineer (3+ years of experience) to join an international project! In this role, you will design, build, and deploy production-scale machine learning and Generative AI / LLM-based applications in a cloud-native environment.
---
๐ Workload: Full-time (100% Remote)
๐ฃ Language: English (Fluent โ daily technical communication)
๐ป Tech Stack: Python, AWS (SageMaker), Docker, Kubernetes, PySpark, FastAPI/Flask, MLOps (MLflow / Kubeflow), LLMs
๐ Location: Remote within EU (must hold EU Citizenship, PR, or a valid EU Work/Residence Permit)
---
๐ฏ Key Responsibilities:
* Design, develop, and deploy production-grade ML and LLM-based applications.
* Build and maintain robust MLOps platforms and CI/CD pipelines for machine learning workflows.
* Automate model training, evaluation, deployment, monitoring, and continuous improvement.
* Develop cloud-native ML infrastructure using AWS, SageMaker, Docker, and Kubernetes.
* Build reliable backend APIs and microservices using FastAPI or Flask.
* Collaborate closely with product, software engineering, and data teams.
---
๐ Requirements:
* 3+ years of commercial experience as an ML Engineer, MLOps Engineer, or in a related field.
* Strong hands-on experience with Python and developing production-ready services with FastAPI / Flask.
* Proven experience with AWS (specifically Amazon SageMaker).
* Hands-on experience with Docker and Kubernetes for deployment and orchestration.
* Solid understanding of MLOps practices and ML lifecycle tools (MLflow, Kubeflow, or SageMaker Pipelines).
* Practical experience working with LLMs / Generative AI in production environments.
* Hands-on experience with PySpark / Apache Spark.
* Fluent English (B2+/C1) for effective collaboration with cross-functional teams.
โญ๏ธ Nice to Have:
* Experience with recommendation systems, NLP, or forecasting use cases.
* Knowledge of model monitoring and observability tools.
---
๐ฉ To Apply:
Send your CV and expected hourly rate to @elizabeth_interexy
#vacancy #AI #MLEngineer #ML
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