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Jeden Abend wirft der Handel Ware weg, die niemand bestellt hat. Und gleichzeitig steht jemand vor einem leeren Regal. Beides sind Planungsfehler und beide lassen sich rechnen. Genau das machen wir bei Circly:…
Analyze structured/unstructured data, build features, and support ML model governance for TD’s homeownership products using Python, Databricks, and open-source libraries.
Build and deploy AI models from scratch for early-stage startups, leading RAG pipelines, agent architectures, and LLM-powered systems in Python with PyTorch/TensorFlow.
Leads a Risk Data Science team at a bank, building credit-risk models (PD, LGD, scoring), fraud detection, and early-warning systems using Python, ML, and SQL.
Builds and validates AI/ML models for U.S. Special Operations Command, focusing on predictive analytics and NLP to forecast resource needs and support mission planning.
Build and operate the data, features, and GenAI foundations for Human Capital AI products, shipping production pipelines and LLM applications using Claude, GPT, and Gemini-class models with strong governance and observability.
Builds high-performance geolocation services for TikTok’s local merchant features using GPS, Wi-Fi, and IP signals, microservices, and LLM-powered workflows.
Build and deploy production-grade ML models for retail, pricing, and operations analytics using Python, SQL, and Azure ML.
Senior AI/ML engineer building and scaling Bank of America’s enterprise Generative AI platform, including LLMs, RAG, agentic workflows, and cloud-native data/AI services.
Build and optimize AI/ML models for retail demand forecasting and supply-chain planning using Python/R, time-series methods, and optimization algorithms.
Build and improve demand-forecasting models using Python and SQL, collaborating with engineers and business teams to deploy multivariate algorithms and enhance supply-chain decisions.
Lead data engineering and analytics for fraud risk at a major African bank, building scalable platforms, ML models, and real-time detection systems to prevent financial crime.
Build and deploy ML models (XGBoost, NLP, deep learning) in AWS to solve client problems, using PySpark, SQL, and MLOps pipelines.
Build and deploy NLP models for federal clients, focusing on text preprocessing, feature engineering, and transformer-based solutions to solve public-sector challenges.
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 deploy ML models for demand forecasting, customer experience, and operations optimization in a B2B and digital commerce setting using Python, SQL, and MLOps.
Build and deploy AI/ML models for enterprise search, including ranking, semantic search, and generative AI features, to improve product discovery and user experience.
Build and deploy ML models for demand forecasting, customer experience, and operations optimization in a B2B and digital-commerce setting using Python, SQL, and MLOps pipelines.
Build and secure AI/ML systems for national defense, including LLM apps, predictive models, and adversarial defenses, using Python, TensorFlow/PyTorch, and edge deployment tooling.
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