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Build and deploy enterprise Generative AI apps using LLMs, RAG pipelines, and AI agents with Python, LangChain, and vector databases.
Design and deploy AI-powered applications, including LLM-based agents and workflows, to transform enterprise processes while ensuring scalability, security, and governance.
Build and deploy ML models for credit risk scoring and fraud detection using Python, SQL, and gradient boosting; work with large credit-history datasets in production.
Build and deploy ML models for Weekday AI’s core product, focusing on model training, optimization, and integration into scalable AI systems.
Build and scale the core ML systems for a new AI startup, designing models and infrastructure from the ground up.
Build and optimize data pipelines and infrastructure for Prima’s motor insurance platform, using Python, Spark, Kafka, and AWS to support analytics and ML workflows.
Мы ищем ML-инженера , который будет разрабатывать и внедрять модели машинного обучения для задач прогнозирования. Вы присоединитесь к команде, которая строит системы, помогающие бизнесу принимать решения на основе…
Design, build, and deploy AI/ML models and services, including generative AI and RAG systems, while ensuring responsible AI practices and robust MLOps pipelines.
Build and optimize cloud data pipelines and warehouses (Snowflake/BigQuery) to power AI-driven analytics and BI for global consumer brands.
Build and maintain scalable data pipelines, ETL/ELT workflows, and Tableau dashboards to transform raw data into actionable insights for clients.
Builds end-to-end data pipelines in Snowflake and AWS, transforming raw data into AI-ready features for an internal AI platform used across marketing and analytics workflows.
Build and deploy data pipelines, cloud data platforms, and ML systems for clients using Databricks, Spark, AWS, and MLOps tooling.
Build and maintain scalable data pipelines and ETL processes to power AI model training and analytics at a cutting-edge AI company.
Build and maintain full-stack apps integrating AI modules (RAG, agents) using React, Node.js, and Python; design scalable APIs, manage data pipelines, and deploy on cloud.
Build and maintain secure Java backend services that power Barclays’ mobile and online banking, using modern engineering practices.
Build and scale ML infrastructure for a quantitative trading firm, designing feature stores, MLOps pipelines, and data lakes to support petabyte-scale time-series models in low-latency environments.
Build and optimize machine learning models and AI solutions using Python and ML libraries in a remote UK role for entry-level engineers.
Principal GCP Data Engineer designs and builds scalable data pipelines using BigQuery, Dataflow, and Dataproc, leading teams to deliver robust, cloud-native solutions for clients.
Build and maintain scalable Java backend services for Barclays’ mobile and online banking platforms, using TDD and RESTful APIs.
Design, build, and deploy enterprise-scale AI/ML solutions using Python, SQL, and frameworks like TensorFlow/PyTorch, with cloud platforms (Azure/AWS/GCP) and MLOps practices.
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