Lead Data Scientist

🧠 Lead Data Scientist – Computer Vision & AI Platforms 🌎 Location: LATAM (Remote)🧠 Seniority: Lead / Principal-Level 🏭 Focus Area: Computer Vision · AI Platforms · Manufacturing Intelligence ⭐ Role Highlights Foundational AI Role: Lead the computer vision intelligence layer of an AI-powered manufacturing platform End-to-End Ownership: Combine vision modeling, data engineering, and MLOps to deliver production AI systems Modern AI Stack: Azure Machine Learning, Databricks, multimodal models, and agentic AI frameworks 🔍 Summary We are seeking a Lead Data Scientist to drive the computer vision capabilities of an AI-powered manufacturing intelligence platform. 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 . This is a highly cross-functional, hands-on leadership role and is foundational to the platform’s intelligence layer. 🛠 Required Skills & Experience Computer Vision & Deep Learning Strong experience building, training, and evaluating CNNs, transformers, or multimodal models Use cases including image classification, feature extraction, defect detection, and segmentation 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 Additive manufacturing experience not required — applied vision experience is key Data Engineering for AI Demonstrated ability to build data pipelines that support ML workflows, including: Large-scale image ingestion Feature extraction and embedding generation Schema and metadata alignment Delta Lake pipelines Feature engineering and feature store integration Automated data validation and drift checks Azure ML & MLOps Hands-on experience deploying, monitoring, and managing models using Azure Machine Learning Experience with: Model versioning Batch inference jobs and online endpoints Environment management Automated training pipelines Databricks & Distributed Processing Proficiency in SQL and PySpark Experience with distributed compute patterns for large image and metadata datasets Agentic AI & Orchestration Familiarity with LangChain, LangGraph , or similar frameworks for tool-using AI agents and multi-step workflows Model Observability & Drift Detection Experience implementing monitoring and drift detection using: Azure ML Monitoring Application Insights Custom statistical techniques Software & Data Foundations Strong Python engineering skills Solid understanding of APIs and microservices Experience with structured and unstructured data modeling Ability to produce reproducible ML workflows ➕ Preferred Skills & Experience 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 Understanding of secure ML development practices aligned with NIST 800-53 Prior leadership experience mentoring junior data scientists and collaborating with data and platform engineers 🎓 General Requirements Education: Master’s or Ph.D. preferred in Computer Science, Data Science, Engineering, or related field Experience: 7+ years in machine learning or applied data science 3+ years focused on computer vision 3+ years building data engineering pipelines for ML Soft Skills: Excellent communication and architectural thinking Ability to influence engineering and product teams Comfortable operating in a fast-paced, iterative delivery environment 🌟 Why Join Us Platform-Defining Role: Own the intelligence layer powering AI-driven manufacturing decisions Advanced AI Challenges: Multimodal reasoning, vision + metadata, agentic workflows Modern Infrastructure: Azure ML, Databricks, distributed compute, production MLOps Remote LATAM Opportunity: Work remotely while collaborating with global product and engineering teams Leadership & Impact: Shape technical direction while remaining deeply hands-on 🏢 About Us We work with innovative teams building next-generation AI platforms that solve complex, real-world problems. Our approach emphasizes production-ready AI , strong data foundations, and close collaboration across product, engineering, and data science. We value ownership, clarity, and measurable impact.