Lead Data Scientist: Computer Vision & AI Platforms (Remote LATAM)

Elios Talent; A distancia; MXN 1,618,000 - 2,339,000; Jornada completa

Descripción de la vacante

A leading talent acquisition firm is seeking a Lead Data Scientist with expertise in Computer Vision and AI Platforms for a remote position in LATAM. The ideal candidate will have significant experience building AI systems, managing data engineering pipelines, and working with Azure Machine Learning. This role involves leading the vision intelligence for an AI-powered manufacturing platform and requires strong skills in CNNs, MLOps, and collaboration with global teams.

Formación

• 7+ years of experience in machine learning or applied data science.
• 3+ years of experience building data engineering pipelines for ML.
• Prior leadership experience mentoring junior data scientists.

Responsabilidades

• Lead the computer vision intelligence layer of an AI-powered manufacturing platform.
• Deliver production AI systems with Azure Machine Learning and Databricks.
• Assess manufacturability and printability from images and schematics.

Conocimientos

Building, training, and evaluating CNNs

Proficiency with PyTorch and/or TensorFlow

Data Engineering for AI

Deployment with Azure ML & MLOps

SQL and PySpark

Python engineering skills

Experience with structured and unstructured data modeling

3D or geometric data experience

Mentoring and collaborative skills

Educación

Degree in Computer Science, Data Science, Engineering or related field

Herramientas

Azure Machine Learning

Databricks

Agentic AI frameworks (e.g., LangChain, LangGraph)

Descripción del empleo

A leading talent acquisition firm is seeking a Lead Data Scientist with expertise in Computer Vision and AI Platforms for a remote position in LATAM. The ideal candidate will have significant experience building AI systems, managing data engineering pipelines, and working with Azure Machine Learning. This role involves leading the vision intelligence for an AI-powered manufacturing platform and requires strong skills in CNNs, MLOps, and collaboration with global teams.