Lead Data Scientist

hace 1 semana


WorkFromHome, México Elios Talent A tiempo completo

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. #J-18808-Ljbffr


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