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Build and deploy AI/ML models and data pipelines to power logistics solutions, working with Python, cloud platforms, and MLOps tools.
Designs and deploys ML models for localization workflows using Python, TensorFlow, and AWS services; owns projects from conception to production.
Build and deploy AI/ML models to automate business processes and generate insights from ERP data using frameworks like TensorFlow or PyTorch.
Builds scalable backend services for a real-time AI/ML platform using Java/Spring Boot, RESTful/GraphQL APIs, and cloud infrastructure.
Builds and maintains AI/ML pipelines and production systems to address environmental, public health, and forensic challenges using data science.
Build and deploy AI/ML models and MLOps pipelines to tackle public health and forensic challenges using Python/R, Azure, Kubernetes, and MLFlow.
Build and deploy ML models that turn multi-modal retail data into security insights using PyTorch, scikit-learn, and Kubernetes on a cloud-native platform.
Build and deploy AI/ML models and MLOps pipelines to tackle environmental, public-health and forensic challenges for New Zealand’s government research agency.
Build and deploy ML models to detect retail crime patterns, match suspects, and analyze video evidence for global retail clients using Python, computer vision, and cloud pipelines.
Build and operate CI/CD pipelines and AI-enabled tooling for a platform that helps job seekers and employers match efficiently.
Build and deploy ML models for predictive analytics and data-driven decision-making using Python or R.
Build and deploy ML models to solve logistics and storage optimization problems for a climate-focused storage provider in Denmark.
Build and deploy ML models using TensorFlow or PyTorch to create data-driven solutions in collaboration with data scientists and engineers.
Build and deploy transformer-based NLP models for financial text extraction, owning end-to-end pipelines from data labeling to production deployment.
Build Palette’s AI-native signal engine: ingest team tool data, model it as a queryable graph, and power shared context for both humans and agents using LLMs and vector search.
Build and deploy production-grade ML systems from validated prototypes, focusing on scalable analytics for consumer insights and brand management using Python and statistical modeling.
Design and deploy ML systems and predictive models using Azure MLOps and NLP for client projects.
Build and deploy scalable AI/ML models and LLM-based systems on Hilti’s AI platform, using Python, Azure, and MLOps/LLMOps practices to power global construction workflows.
Build AI/ML systems for Grab’s food-delivery platform, including demand shaping, content enrichment, and generative AI features to improve user experience and platform efficiency.
Lead the design and deployment of AI/ML solutions using Azure ML, OpenAI APIs, and Generative AI for computer vision tasks like object detection and retail shelf analysis.
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