Descrição da Função

Were hiring Senior AI/ML Engineer MLOps & GenAI Ops

Join a global technology leader in a fully remote role based in Portugal. This is a direct hire opportunity to lead cutting-edge initiatives in MLOps, GenAI Ops, Azure Cloud, and Snowflake supporting enterprise-scale AI innovation.

Location Remote (Portugal-based)

Contract Permanent direct hire with our client

Youll be responsible for designing, deploying, and scaling production-grade AI/ML ecosystems. From operationalizing GenAI models to building robust pipelines and cloud-native architectures, this role blends deep technical expertise with strategic impact.

Key Responsibilities

• Develop and maintain ML pipelines for training, validation, deployment, and monitoring of models.
• Support scalable ML solutions across use cases like recommendations, forecasting, and automation.
• Work with tools like Airflow, Azure ML, and FastAPI to deliver production-ready systems.
• Automate model deployment workflows using CI/CD tools (e.g. GitHub Actions, Azure DevOps).
• Contribute to the reliability, observability, and performance of the ML platform.
• Collaborate with data scientists to productionise research code and models into scalable services.
• Help implement monitoring, alerting, and model drift detection using tools like NewRelic, Azure Monitor, and custom logging frameworks.
• Continuously improve and manage infrastructure using Terraform, Docker, and Fargate.

What Were Looking For

• Proven experience in ML Engineering, DevOps, or Data Engineering with exposure to ML lifecycle.
•  Hands-on experience building or maintaining ML workflows or pipelines.
• Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch.
• Familiarity with cloud platforms (especially Azure, AWS).
• Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes).
• Exposure to CI/CD tools (GitHub Actions, Azure DevOps) and infrastructure-as-code (Terraform).
• Collaborative team player with excellent communication skills.

Nice to Have

• Knowledge of data platforms (e.g. Snowflake, Azure Data Lake).
• Experience deploying models as APIs (FastAPI, Azure Functions).
• Understanding of monitoring, model performance tracking, and observability best practices.
• Familiarity with orchestration tools like Airflow or Azure Data Factory.

Ready to lead AI innovation from Portugal? Apply now and shape the future of enterprise AI.

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