Top Tech Jobs & Startup Jobs

Develops and drives reliability for low-voltage automotive electronics from concept through production. Responsibilities include establishing design-for-reliability guidelines, identifying failure modes, developing validation and accelerated testing strategies, leading root-cause investigations, auditing contract manufacturers, and analyzing fleet and field data. The role requires expertise in electronics reliability, FMEA, statistical reliability analysis, failure mechanisms, thermal management, interconnects, and failure-analysis techniques.

Leads cross-functional technical programs across mapping, vehicle access, mobile applications, and fleet services spanning cloud, mobile, and vehicle firmware. Responsibilities include managing schedules, priorities, dependencies, risks, technical feasibility, stakeholder expectations, and execution plans; influencing engineering and product teams; and removing obstacles to deliver business-critical software programs.

Design, deploy, and maintain global data platform infrastructure with emphasis on multi-region Databricks orchestration. Lead system architecture, optimize Databricks (Delta, Spark, Unity Catalog), implement IaC with Terraform, build CI/CD pipelines, troubleshoot platform issues, and collaborate with cross-functional teams to meet technical, governance, and performance requirements.

Contribute to customer-facing infotainment, mobile, and connectivity software for Rivian vehicles. Responsibilities include developing and testing features, writing code in Kotlin, Java, C++, or Python, debugging issues, collaborating with product and design teams, and presenting progress. Potential projects include Android Automotive applications, platform software, wireless and telematics integration, 3D graphics, and automated integration testing.

Work on backend services, distributed systems, connectivity infrastructure, and integration software connecting vehicles, mobile apps, and cloud platforms. Responsibilities include developing and testing software in Python, Go, C++, or Java; contributing to event-driven systems, AWS cloud infrastructure, test automation, validation, code reviews, debugging, documentation, and project presentations.

Integrate, commission, debug, and validate automotive software and hardware systems across prototype vehicles, lab cars, and production launches. Diagnose system-level issues spanning multiple ECUs and software domains, perform root-cause analysis, assess component and system risks, and collaborate with architecture, platform, and application engineering teams to resolve dependencies and integration blockers.

Lead vehicle power-mode architecture and system integration across software, hardware, diagnostics, validation, manufacturing, and partner teams. Translate vehicle behavior into requirements, state machines, and integration plans; coordinate dependencies and release readiness; investigate issues using CAN, LIN, Automotive Ethernet, vehicle logs, and ECU diagnostics; improve observability; and drive system integration through production-ready firmware releases.

Design, develop, optimize, and debug embedded software for automotive ECUs and development boards running Linux, Android, or RTOS environments. Work on drivers, bootloaders, board support software, hardware abstraction layers, firmware security, camera software, kernel features, automated testing, and CI integrations. Collaborate with hardware and vehicle systems engineers, document technical work, and present progress during the internship.

Supports ECU hardware projects across circuit design, mechanical packaging, validation, troubleshooting, functional safety, supplier quality, product launch, and manufacturing readiness. Responsibilities include debugging board- and system-level issues, documenting component releases, maintaining design records, collaborating with cross-functional teams, and communicating project progress. Candidates must be enrolled in a bachelor’s or master’s program and have strong electrical engineering fundamentals.

Data Engineering Interns will build and maintain data pipelines, analytics workflows, and machine learning infrastructure. Responsibilities include writing Python and SQL for data transformation and validation, developing automated data quality tests, supporting CI/CD, collaborating with data scientists and engineers, and documenting project progress. Assignments may support fleet management, manufacturing execution, vehicle telemetry, analytics, or AI/ML platforms.