Top Software Engineer Jobs in Detroit, MI

The Vice President will lead engineering teams for the commercial data platform, drive strategic data initiatives, and collaborate across functions to enhance data reliability and governance.

The AI Engineer designs, develops, and deploys AI-driven applications for non-data scientists, enhancing decision-making and model accessibility for organizations.

The Product Engineer will build decentralized finance applications, focusing on full-stack mobile and web experiences using React and React Native, while also developing tooling and infrastructure in a fast-paced environment.

The Solution Engineer will design and implement data quality solutions, work directly with customers, and optimize integrations within their data ecosystems, utilizing Python and modern tools while communicating technical concepts effectively.

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

Dapper Labs seeks curious and ambitious individuals to engage in various roles focused on digital ownership, gaming, and community building. Responsibilities include designing user experiences, crafting marketing strategies, and growing user communities. Candidates must thrive in ambiguity, work collaboratively, and share their passions with the team.

The Senior Software Engineer will lead development, mentor engineers, and create data solutions using TypeScript, React, and Python. Responsibilities include designing applications, driving innovation, and ensuring high-quality user experiences.

Build scalable backend services and data pipelines to process large healthcare datasets, integrate and optimize LLM-driven features, implement observability and best practices, collaborate across frontend, data, and AI teams, and own end-to-end feature delivery for production systems.

Design, build, and operate scalable web applications, APIs, services, and AI-enabled workflows. Use AI tools across the development lifecycle, ensure reliability, performance, and observability, contribute to technical decisions, iterate from user feedback, and own production quality and delivery as part of cross-functional squads.

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