Lead engineering across ML/MLOps and core software development: define strategy, scale ML platforms, integrate ML lifecycle with CI/CD and Kubernetes, ensure software engineering best practices, mentor distributed teams, and collaborate cross-functionally to deliver product vision.

Seeking a Senior Data Engineer to design and implement high-performance data solutions and pipelines, ensuring scalability and reliability in cloud environments.

Lead enterprise revenue growth and manage sales teams; architect AI-driven solutions and collaborate with clients to solve business problems.

The Lead Data Engineer designs, builds, and optimizes data integration and analytics infrastructure on Microsoft Azure, collaborating with cross-functional teams to meet business objectives.

This role involves designing, building, and maintaining data integration and analytics infrastructure using Microsoft Azure, focusing on hands-on engineering and solution architecture.

The Lead Data Engineer is responsible for designing and optimizing data infrastructures, building pipelines, and collaborating with cross-functional teams using Microsoft Azure.

The Lead Data Engineer designs and optimizes data infrastructure, builds data pipelines, and collaborates on analytics solutions using Microsoft Azure, ensuring effective data integration and processing.

Data Scientist will develop models for customer retention, demand prediction, and pricing strategies by utilizing machine learning and statistical techniques.

The Lead Data Engineer is responsible for designing and optimizing data infrastructure using Microsoft Azure for data integration and analytics, collaborating closely with cross-functional teams.

The Solution Data Architect designs and implements data integration and analytics infrastructure using Microsoft Azure, ensuring effective data solutions and collaboration with cross-functional teams.

The Applied AI Engineer will develop and deploy AI automation solutions, integrate LLMs, and collaborate with clients to enhance workflows and systems.

As an Applied AI Engineer (Automation), you'll design, develop, and deploy AI and automation solutions, integrating LLMs into workflows and ensuring scalability and client satisfaction.

The Applied AI Engineer will design, develop, and deploy AI solutions, integrating LLMs into business workflows, and ensuring reliability and maintainability of systems.

As an Applied AI Engineer, you will design, develop, and deploy AI automation solutions, integrating LLMs into business workflows, and collaborating with stakeholders. Responsibilities include building reliable systems, supporting clients, and enhancing features.

As an Applied AI Engineer, deliver AI and automation solutions from requirements to deployment, collaborating with stakeholders, designing workflows, and improving deployed systems.

As an Applied AI Engineer, you will design, develop, and deploy AI and automation solutions, collaborating with various stakeholders. Responsibilities include building workflows, integrating LLMs, improving solutions, and producing documentation.

Lead modernization of on-premises systems to cloud architecture, mentor engineers, design data solutions, and ensure data integrity and governance.

The role involves leading cloud-native data solutions, mentoring junior engineers, optimizing data pipelines, and ensuring data quality within Azure frameworks.

Design and maintain infrastructure for advanced analytics and data integration. Implement Google Cloud's Unified Graph Fabric and build a Customer 360 Knowledge Graph.

The Senior Data Engineer will design and maintain graph-based data infrastructures, focusing on customer analytics using Google Cloud and BigQuery, alongside graph algorithms and data pipelines.