Production ML Engineer — Ranking & Retrieval

ActAI; United States; Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

ActAI is building AI-native applications and powering smart assistants with production ML systems. We seek engineers who tackle practical ML problems, improve model quality and ship reliable systems used by real users.

You will work on classification, retrieval, ranking, and personalization, taking ownership from model development to production deployment. The role emphasizes efficient, scalable ML pipelines and robust evaluation.

Formación

• Strong foundations in machine learning and neural architectures.
• Hands-on experience deploying ML models to production.
• Experience in classification, ranking, retrieval, or personalization.
• Understanding of model evaluation, experimentation and performance metrics.
• Production-quality code and real-world datasets.

Responsabilidades

• Build and improve ML models for classification, ranking, retrieval and personalization.
• Develop efficient classifiers optimizing accuracy, latency and cost.
• Improve search relevance and context retrieval using embeddings and hybrid search.
• Build personalization models that learn from user behavior while respecting privacy.
• Develop evaluation pipelines, labeled datasets and metrics to measure model quality.
• Fine-tune and adapt existing models with sufficient data.
• Build and maintain ML training, inference and deployment pipelines.
• Debug production issues and monitor model performance.

Conocimientos

ML foundations

Production ML

Python

PyTorch

JAX

Embeddings

Vector search

Retrieval

Ranking

Personalization

Herramientas

Python

PyTorch

JAX

Embeddings

Descripción del empleo

ActAI is building AI-native applications and powering smart assistants with production ML systems. We seek engineers who tackle practical ML problems, improve model quality and ship reliable systems used by real users.

You will work on classification, retrieval, ranking, and personalization, taking ownership from model development to production deployment. The role emphasizes efficient, scalable ML pipelines and robust evaluation.