ML Engineer – Ranking & Retrieval for AI Apps

ActAI; Portugal; On-site; EUR 55,000 - 90,000; Full time

Job summary

ActAI is building AI-native applications and seeks an ML Engineer to develop and productionize ML models for classification, ranking, and personalization. You will work on embeddings, vector search, and evaluation pipelines, taking ownership from model development to production deployment.

The role focuses on practical ML problems, improving model quality, and shipping reliable systems used by real users. Strong Python and PyTorch/JAX skills are essential in a fast-paced, collaborative

Qualifications

• Strong foundations in machine learning and modern neural architectures.
• Hands-on experience building and deploying ML models in production.
• Experience in classification, ranking, retrieval, recommendation systems or personalization.
• Understanding of model evaluation, experimentation and performance metrics.
• Comfortable writing production-quality code and working with real-world datasets.
• Able to balance model quality, latency, cost and reliability.
• Strong ownership, problem-solving skills

Responsibilities

• Build ML models for classification, ranking, retrieval and personalization.
• Develop evaluation pipelines, labeled datasets and metrics to measure model quality.
• Fine-tune and adapt existing models when supported by sufficient data.
• Build and maintain ML training, inference and deployment pipelines.
• Debug production issues, monitor model performance and ship improvements based on real-world feedback.
• Collaborates effectively with engineering and product teams to deliver reliable ML-powered features.

Skills

Machine Learning Fundamentals

Production ML

Python

Model Evaluation

Tools

PyTorch

JAX

Embeddings/Vector Search

Ranking Models

Job description

ActAI is building AI-native applications and seeks an ML Engineer to develop and productionize ML models for classification, ranking, and personalization. You will work on embeddings, vector search, and evaluation pipelines, taking ownership from model development to production deployment.

The role focuses on practical ML problems, improving model quality, and shipping reliable systems used by real users. Strong Python and PyTorch/JAX skills are essential in a fast-paced, collaborative