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Builds and deploys ML models to forecast demand, automate order generation, and optimize inventory/production for a restaurant chain, reducing waste and improving operational efficiency.
Design and implement advanced analytics and predictive models for regulated public-sector projects using Python, AWS SageMaker, and SQL.
Design and enforce AI security controls for an AI-first enterprise platform, including agent governance, model risk management, and ML-driven threat detection across 500+ customer environments.
Build and deploy ML models (XGBoost, NLP, deep learning) in AWS to solve client problems, using PySpark, SQL, and MLOps pipelines.
Build, deploy, and monitor ML models end-to-end using Python, scikit-learn, and cloud platforms to drive business impact in insurance and financial services.
Design and build AI-powered applications using cloud services, generative models, and deep learning pipelines in production environments.
Build and own production ML/AI components for Amgen’s AI Studio, including GenAI, RAG, and retrieval systems, using Python, SQL, and cloud services.
Build and deploy production ML and GenAI components—models, RAG systems, agents, and pipelines—using Python, SQL, and cloud services to power Amgen’s healthcare-focused AI products.
Build, deploy, and monitor ML models and MLOps pipelines on AWS for forecasting and GenAI apps in a biotech setting.
Summary Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first…
Build predictive models for military logistics, including demand forecasting and inventory optimization using time-series and ML techniques.
Builds and deploys autonomous AI agents, multi-agent systems, and generative AI solutions using frameworks like LangChain, AutoGen, and Azure OpenAI to automate enterprise workflows, enhance decision-making, and deliver scalable AI-driven business value.
Lead a team of ML engineers and architects at an AI-first cloud services company, owning hiring, team growth, and complex customer engagements while shaping AI/ML architectures and driving pre-sales.
Build and deploy ML models to match renters with properties, optimize marketplace performance, and drive revenue growth using Python, SQL, and ML frameworks.
Build predictive and recommendation models (churn, AML, personalization) using Python, Spark, and MLOps in a fintech context.
Builds ML models for personalized loan pricing, using uplift modeling, reinforcement learning, and A/B testing to optimize interest rates and maximize bank profit.
Data Scientist (Brooklyn Nets - Basketball Operations) Location: Brooklyn, NY 11232 Department: Basketball Operations SUMMARY The Brooklyn Nets Basketball Operations department is seeking a passionate, creative, and…
Build and deploy ML models for edge and bare-metal devices, focusing on sensor fusion (audio, video, radio) to detect drones in production environments using Python, PyTorch/TensorFlow, and cloud/AWS/GCP.
Senior Data Scientist working in an insurance company's pricing team, creating innovative pricing models using complex data sources with Python, SQL, AzureML, and XGBoost. The role involves working 1 day a week in London or Leicester in a small team of 6 people on experimental pricing approaches.
Build statistical and ML models for healthcare analytics and pharma marketing mix modeling to optimize spend and strategy using Python, SQL, and cloud tools.
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