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Build and own Hive’s cloud-native data and ML platforms handling billions of event-attendee interactions yearly, using Python, ClickHouse, Airflow, and LLM-powered pipelines to power real-time marketing automation for 1,500+ events.
Build and evaluate AI systems by designing grading criteria for data science deliverables and assessing AI-generated or human-created work against those standards.
Build and deploy end-to-end ML systems—from data pipelines to production models—using Python and libraries like Pandas, Scikit-learn, and PyTorch.
Build and maintain ML pipelines that detect anomalies in healthcare claims and pharmacies using Python, FastAPI, and unsupervised models (KMeans/DBSCAN) with Oracle data pipelines.
Lead AI engineering for an insurance platform, building LLM-driven audit and claims automation, scalable ML pipelines, and generative AI applications while ensuring compliance and performance.
Senior Data Engineer builds and optimizes cloud-based data pipelines and warehouses using AWS, Snowflake, Matillion, and dbt to power analytics and AI at Philip Morris International.
Build and ship production-grade agentic AI systems in Python, integrating LLMs with tools, memory, and multi-agent workflows on Azure AI Foundry for real customer use cases.
Lead a data science team to analyze business performance, build predictive models, and automate decisions for a fintech company specializing in small business lending.
Build and deploy production-grade machine learning systems for ad-targeting and analytics using Databricks, MLFlow, and cloud infrastructure.
Build and deploy generative AI models and LLM-based systems on AWS for clients, focusing on production-grade RAG, agentic workflows, and ML pipelines.
Designs and implements AI solutions using LLMs and data pipelines, collaborating with teams to solve business problems through AI-driven architectures.
Eurowag is building a credit decisioning capability that will underpin credit risk lending decisions across multiple products and markets. This role is the core of that capability. The Credit Decisioning Analyst will…
Lead a team of ML engineers to design, build, and deploy scalable machine learning models for RBC Wealth Management, using Python, Java, AWS/Azure, and MLOps practices.
Build and deploy generative AI and agentic systems for a global gaming company, selecting LLMs, fine-tuning models, and driving production-grade AI solutions.
Lead a greenfield Applied AI team to build production-grade ML and LLM-augmented models for wealth-management workflows, owning the full lifecycle from problem framing to deployment and monitoring.
Build and maintain scalable data pipelines on Google Cloud, model BigQuery warehouses, and collaborate with ML teams to deploy models via Vertex AI.
Build and scale high-performance ML systems for real-time fraud detection using PyTorch/TensorFlow and multi-GPU training pipelines, while mentoring engineers and shaping data architecture.
Build and deploy ML/AI models (including GenAI) for pricing, personalization, and fraud detection in a restaurant-tech SaaS platform.
Build and scale a feature platform that powers real-time ML ad recommendations, handling batch and streaming pipelines with Python, Flink, and Spark to serve low-latency features for model inference.
Build and deploy enterprise-grade AI and ML solutions, including Generative AI apps with LLMs, RAG, and vector databases, to solve complex business problems for SAP customers.
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