AI Summary
Design, implement and maintain scalable MLOps platforms for enterprise AI solutions. Build automated ML pipelines, CI/CD workflows, and production infrastructure for LLMs and generative AI. Requires 4+ years of MLOps experience, Python proficiency, and cloud-native expertise.
Key Highlights
Build and maintain scalable MLOps platforms
Develop automated ML pipelines and CI/CD for production deployment
Support LLMs and generative AI with cloud-native infrastructure
Key Responsibilities
Design, implement and maintain scalable MLOps platforms
Build automated Machine Learning pipelines for training, testing, deployment and monitoring
Develop CI/CD pipelines for Machine Learning applications
Deploy AI and Machine Learning models into production environments
Monitor model performance, drift detection and operational health
Manage model versioning, experiment tracking and reproducibility
Implement Infrastructure as Code (IaC) and cloud-native automation
Optimize cloud infrastructure for performance, security and cost efficiency
Establish governance, monitoring and security best practices across AI environments
Drive continuous improvements in platform reliability and operational excellence
Technical Skills Required
Benefits & Perks
Fully remote or hybrid working model within Portugal
Competitive salary package
Annual performance bonus
Private healthcare
Learning and certification budget
Flexible working environment
Nice to Have
Experience supporting Large Language Models (LLMs)
Experience with Retrieval-Augmented Generation (RAG)
Familiarity with LangChain or LangGraph
Knowledge of Vector Databases (Pinecone, Weaviate, ChromaDB, Milvus)
Experience with NVIDIA AI infrastructure
Experience in highly regulated industries
Kubernetes certifications (CKA or CKAD)
Cloud certifications (AWS, Azure or Google Cloud)
Job Description
NexyaHR is conducting an exclusive search on behalf of an international technology organization seeking an experienced MLOps Engineer to support the deployment, automation and lifecycle management of enterprise Artificial Intelligence platforms.
This role is ideal for professionals passionate about building scalable Machine Learning infrastructure, automating model deployment and enabling AI teams to deliver production-ready solutions efficiently and securely.
Working alongside Data Scientists, AI Engineers, Software Engineers and Cloud Architects, you will play a critical role in designing robust MLOps ecosystems that support the full machine learning lifecycle.
Key Responsibilities
- Design, implement and maintain scalable MLOps platforms.
- Build automated Machine Learning pipelines for model training, testing, deployment and monitoring.
- Develop CI/CD pipelines for Machine Learning applications.
- Deploy AI and Machine Learning models into production environments.
- Build infrastructure supporting Large Language Models (LLMs) and Generative AI applications.
- Monitor model performance, drift detection and operational health.
- Manage model versioning, experiment tracking and reproducibility.
- Collaborate with Data Scientists to optimize production workflows.
- Implement Infrastructure as Code (IaC) and cloud-native automation.
- Optimize cloud infrastructure for performance, security and cost efficiency.
- Establish governance, monitoring and security best practices across AI environments.
- Drive continuous improvements in platform reliability and operational excellence.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence or a related discipline.
- Minimum of 4 years’ experience in DevOps, Cloud Engineering, Platform Engineering or MLOps.
- Strong programming skills in Python.
- Experience with Docker and Kubernetes.
- Hands-on experience with CI/CD tools such as GitHub Actions, GitLab CI, Azure DevOps or Jenkins.
- Experience deploying Machine Learning models in production.
- Strong knowledge of AWS, Microsoft Azure or Google Cloud Platform.
- Experience with Infrastructure as Code (Terraform, Pulumi or CloudFormation).
- Familiarity with MLflow, Kubeflow, SageMaker, Vertex AI or Azure Machine Learning.
- Experience with monitoring and observability tools such as Prometheus, Grafana, ELK or Datadog.
- Knowledge of container orchestration and cloud-native architectures.
- Strong understanding of software engineering best practices.
- Excellent analytical and troubleshooting skills.
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- English — C2 level (mandatory)
Nice to Have
- Experience supporting Large Language Models (LLMs).
- Experience with Retrieval-Augmented Generation (RAG).
- Familiarity with LangChain or LangGraph.
- Knowledge of Vector Databases (Pinecone, Weaviate, ChromaDB, Milvus).
- Experience with NVIDIA AI infrastructure.
- Experience in highly regulated industries.
- Kubernetes certifications (CKA or CKAD).
- Cloud certifications (AWS, Azure or Google Cloud).
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Opportunity to join an international technology organization.
- Fully remote or hybrid working model within Portugal.
- Competitive salary package.
- Annual performance bonus.
- Private healthcare.
- Learning and certification budget.
- Access to modern AI and cloud technologies.
- Flexible working environment.
- International projects with multidisciplinary teams.
- Long-term career progression.
As organizations accelerate the adoption of Artificial Intelligence, MLOps has become one of the most critical disciplines in modern software engineering. This role offers the opportunity to build enterprise-scale AI platforms, automate Machine Learning operations and contribute to the successful deployment of cutting-edge AI solutions within an international and innovation-driven environment.
Equal Opportunities
NexyaHR is proud to partner with organizations committed to diversity, equity and inclusion. We welcome applications from all qualified professionals regardless of gender, age, disability, ethnicity, religion or sexual orientation.
All applications will be treated with the strictest confidentiality.
Skills: azure,infrastructure,software,artificial intelligence,machine learning,cloud
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