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2 Days Ago
Columbus, OH, USA
9 Employees
Junior
9 Employees
Junior
Artificial Intelligence • Cloud • Database • Analytics
The Splunk/Cribl Developer is responsible for designing and implementing Cribl pipelines, integrating with Splunk, and optimizing performance. Key tasks include troubleshooting issues, collaborating with teams, and ensuring integration with data sources. Staying updated on technologies and explaining technical concepts to various audiences is essential.
2 Days Ago
Chicago, IL, USA
9 Employees
Mid level
9 Employees
Mid level
Artificial Intelligence • Cloud • Database • Analytics
The Quantitative Data Scientist will develop quantitative financial investment models and algorithms while managing large datasets. The role requires working cross-functionally with software engineers and product managers to support quantitative analyses through integration of diverse data sources.
2 Days Ago
Alpharetta, GA, USA
9 Employees
110K-130K Annually
Senior level
9 Employees
110K-130K Annually
Senior level
Artificial Intelligence • Cloud • Database • Analytics
As a Data Engineer, you will design and maintain scalable data pipelines using Java and Spark, optimize SQL queries, and implement solutions with Snowflake. You'll collaborate with teams to understand data requirements and ensure efficient data processes, and may develop visualizations with Tableau.
19 Days Ago
Plano, TX, USA
9 Employees
110K-130K Annually
Senior level
9 Employees
110K-130K Annually
Senior level
Artificial Intelligence • Cloud • Database • Analytics
As a Senior Java Full Stack Developer, you will design, develop, and maintain applications, focusing on both front-end and back-end technologies. Responsibilities include collaborating with teams, implementing responsive UIs, developing RESTful APIs, and utilizing AWS services for cloud deployment.
19 Days Ago
Charlotte, NC, USA
9 Employees
Senior level
9 Employees
Senior level
Artificial Intelligence • Cloud • Database • Analytics
The AI/ML Engineer will develop Generative and Traditional AI platform capabilities on enterprise and cloud platforms. Responsibilities include delivering AI models to infrastructure, optimizing scoring pipelines, automating model deployment, collaborating with teams for end-to-end model delivery, and providing guidance on software engineering principles. Additional support for production issues is expected.
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