Top Software Engineer Jobs in Tucson, AZ

The Integration Commissioner /Tester will perform Integration and Customer Acceptance testing for Ribbon products, focusing on deploying and integrating Telecom networks. Responsibilities include project delivery, configuration, integration, testing, troubleshooting, and collaborating with engineering teams, while ensuring adherence to project budgets and documentation standards.

Lead the design and development of data architecture supporting data modeling, integration, and delivery standards. Collaborate with cross-functional teams to optimize data lakes, enhance data strategy, and ensure robust analytics usage.

The Senior Data Science Consultant at DesignMind will lead client engagements, build machine learning systems, and mentor teams while communicating with stakeholders. Responsibilities include data modeling, statistical analysis, and delivering insights through documentation and presentations.

The Data Engineer will create and manage data sources, assist with SQL queries for the Analytics team, contribute to project workflows, and develop reporting solutions, enhancing data accessibility for business stakeholders.

As a Staff Back End Engineer at MotiveMetrics, you will develop and maintain customer-facing applications while ensuring high quality and system stability. You will lead and mentor a team, focusing on building distributed systems and scaling them using cloud technologies. Your role will involve designing, deploying, and automating workflows within a fast-paced tech environment.

The Staff Software Engineer will focus on developing and managing cryptographic security tools and libraries at Gemini, enhancing the security of digital assets. Responsibilities include building software for multi-party computation, applying cryptographic methods, maintaining security solutions, and collaborating closely with multiple engineering teams.

As a Lead Engineer in MLOps, you will design and implement MLOps pipelines, manage cloud resources, automate model deployments, and collaborate with data scientists to optimize AI/ML infrastructures while staying updated on industry trends.