Machine Learning Engineer - Remote - Portugal

Horário: Full-Time

We’re looking for a Machine Learning Engineer with 4-5 years of professional experience to develop and deploy scalable ML systems, combining classical Machine Learning with LLM-powered applications and agentic workflows.

What you’ll do:

• Design and deploy forecasting and time series prediction models in production;
• Build and maintain ML pipelines on Azure Databricks, using MLflow for experiment tracking, model versioning and lifecycle management;
• Implement feature engineering workflows, model monitoring, drift detection and automated retraining;
• Develop LLM-powered applications and multi-step agentic workflows using prompt engineering, function calling and frameworks such as LangGraph, CrewAI or OpenAI Agent SDK;
• Design evaluation frameworks for ML models, LLM outputs and agent performance;
• Deploy and scale ML solutions using Azure, Docker and Kubernetes;
• Integrate ML components into microservices architectures, ensuring observability, performance and code quality.

What we’re looking for:

• 4-5 years of professional experience in Machine Learning or AI engineering;
• Strong Python skills and solid object-oriented programming fundamentals;
• Hands-on experience developing and deploying forecasting and time series models;
• Experience with production ML workflows and Databricks;
• Knowledge of LLMs, prompt engineering and agentic systems;
• Experience with Azure, Docker and Kubernetes;
• Understanding of model evaluation, monitoring and drift detection;
• Familiarity with workflow orchestration tools such as Apache Airflow;
• Strong coding practices, automated testing and maintainable software development.

Nice to have:

• Experience deploying LLM applications and AI agents in production;
• Familiarity with LLM observability and tracing tools such as Langfuse;
• Knowledge of LLM inference cost optimisation and token caching;
• Experience with multi-agent orchestration, tool use and CI/CD practices.

Education: Degree in Computer Science, Data Science or a related field, or equivalent professional experience.

Vaga em regime 100% remoto.