Lead Data Scientist

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

Lead Data Scientist – Computer Vision & AI Platforms

Location: LATAM (Remote) • Seniority: Lead / Principal-Level • Focus Areas: Computer Vision · AI Platforms · Manufacturing Intelligence • Fundacional AI Role: Lead the computer vision intelligence layer of an AI-powered manufacturing platform.

Combine vision modeling, data engineering, and MLOps to deliver production AI systems with Azure Machine Learning, Databricks, multimodal models, and agentic AI frameworks. This role blends advanced vision modeling, multimodal reasoning, and data engineering to assess manufacturability and printability from images, schematics, and part metadata. The ideal candidate brings deep applied computer vision expertise, strong hands‑on experience building data‑engineering pipelines for ML workflows, and a track record of delivering production‑grade AI systems using Azure Machine Learning, Databricks, and agentic AI frameworks such as LangChain and LangGraph.

Habilidades y Requisitos

• Strong experience building, training, and evaluating CNNs, transformers, or multimodal models.
• Proficiency with PyTorch and/or TensorFlow.
• Industrial / Applied Vision background applying computer vision to real‑world imagery, such as inspection, materials identification, part recognition, or manufacturing‑related data.
• Data Engineering for AI: demonstrated ability to build data pipelines that support ML workflows, including automated data validation and drift checks.
• Azure ML & MLOps: hands‑on experience deploying, monitoring, and managing models using Azure Machine Learning batch inference jobs and online endpoints, environment management, and automated training pipelines.
• Proficiency in SQL and PySpark.
• Experience implementing monitoring and drift detection using Azure ML Monitoring.
• Strong Python engineering skills.
• Experience with structured and unstructured data modeling.
• Experience in manufacturing, industrial automation, or mechanical engineering domains.
• Experience working with 3D or geometric data (CAD files, point clouds, meshes, depth imagery).
• Familiarity with vector databases or embedding‑based search systems for multimodal reasoning.
• Experience optimizing models for performance, latency, and cost in production.
• Prior leadership experience mentoring junior data scientists and collaborating with data and platform engineers.
• General Requirements:
• Degree preferred in Computer Science, Data Science, Engineering, or related field.
• 7+ years in machine learning or applied data science.
• 3+ years building data engineering pipelines for ML.
• Experience with Azure ML, Databricks, distributed compute, production MLOps.

Remote LATAM Opportunity: Work remotely while collaborating with global product and engineering teams. Our approach emphasizes production‑ready AI, strong data foundations, and close collaboration across product, engineering, and data science.