AI Engineer (.NET/C# + ML Engineering)

Project overview

Hybrid AI Engineer contract role in Porto (3 days/week onsite) within a Framework & Research team building shared AI/ML services. The position blends strong C#/.NET backend engineering (microservices, databases, APIs) with hands-on ML engineering in Python: preparing data, training and evaluating multiple model types (beyond LLM/RAG), deploying to cloud endpoints/pipelines, and operating models in production with MLOps (monitoring, versioning, CI/CD). Also includes LLM/Transformers work (Hugging Face, RAG, prompt engineering) plus governance/security/privacy guardrails.

Responsibilities

• Design, develop and maintain backend services using C# and.NET/.NET Core.
• Translate business requirements into reliable software and AI/ML solutions.
• Prepare datasets, define features and select suitable modelling approaches.
• Build, train, fine-tune and evaluate different types of machine learning models.
• Work with models such as classification, regression, NLP, time-series, anomaly detection, computer vision and deep learning.
• Develop production ML pipelines using Python and frameworks such as PyTorch, TensorFlow or scikit-learn.
• Deploy models through cloud endpoints, APIs, batch pipelines or edge applications.
• Monitor model performance, data quality and service behaviour in production.
• Apply model versioning, experiment tracking and, where required, retraining processes.
• Develop LLM-based solutions using GPT, Transformers, Hugging Face, RAG and prompt engineering.
• Create proofs of concept using tools such as Jupyter notebooks.
• Design cloud-based architectures using Azure, AWS or equivalent services.

Requirements

• C# and.NET/.NET Core backend development
• Backend service design (APIs, microservices) and database design
• Hands-on machine learning model development (build/train/fine-tune/evaluate)
• Proven experience deploying at least 2 different ML model types beyond LLM/RAG (e.g., classification/regression/time-series/CV/anomaly detection)
• Strong Python for data processing and ML pipelines
• ML frameworks: PyTorch and/or TensorFlow and/or scikit-learn
• Model evaluation, monitoring, experiment tracking and model versioning
• Cloud deployment for ML (Azure/AWS/GCP) and cloud-based architectures
• Cloud ML platforms: Azure ML/Azure AI and/or AWS SageMaker/AWS Bedrock and/or Vertex AI
• Containerization and orchestration: Docker and Kubernetes
• CI/CD and MLOps practices for production ML
• NLP/LLMs: Transformers, Hugging Face, GPT, RAG, prompt engineering
• API security, AI governance, data privacy/guardrails
• Agile/Scrum ways of working
• Fluent English

Project details

• Start: flexible
• Remote: hybrid
• Location: Portugal, PT