特斯拉Full Stack Software Engineer, React+Java

Develop, test and maintain rich web experiences with UIs that address deep domains with high volumes of data. Building reusable components and front-end libraries for future use. Work with backend team to define and integrate APIs. Implement software designs using JavaScript and related technologies. Prepare and execute unit and integration tests. Envision the functional and non-functional requirements to build solutions from scratch. To be able to define technologies, patterns and prototype solutions for new requirements to materialist it as a well functioning project. Build the front-end of applications through appealing visual design. Use test driven development to ensure responsiveness, consistency and efficiency and crafting maintainable testing infrastructure. Build features and applications with a mobile responsive design. Learn and adapt new technologies to quickly develop required POCs and influence.

Job Description We are seeking a highly motivated Full-Stack Engineer to deliver exceptional user experiences for our enterprise clients. The ideal candidate will have strong software engineering skills and expertise across the entire technology stack, including modern front-end frameworks and back-end languages. Excellent interpersonal communication skills and the ability to provide meaningful feedback on technical design are essential. In this role, you will be responsible for end-to-end development of user experiences — from architecture and interactive front-end interfaces to back-end systems. You will collaborate closely with our Product Managers and cross-functional development teams to deliver innovative solutions for enterprise B2B systems. We are looking for passionate individuals who are committed to building scalable, high-quality applications and can execute effectively in a fast-paced environment. Responsibilities： 1. Design, implement, and maintain full-stack applications, including web pages and back-end APIs, ensuring end-to-end functionality. 2. Optimize code across all layers of the technology stack to improve performance, stability, and maintainability. 3. Collaborate with cross-functional teams, including Product Managers, developers, QA engineers, and business stakeholders on enterprise B2B projects. 4. Stay up-to-date with the latest web and enterprise technology trends while maintaining comprehensive design and requirement documentation for B2B systems. 5. Integrate front-end frameworks (e.g., Angular and React) with back-end services (e.g., C# and Node.js) to build scalable and secure enterprise applications.

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing! An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.NVIDIA is hiring senior software engineers in its Infrastructure, Planning and Process Team (IPP), to accelerate AI adoption across various engineering workflows within the company. IPP is a global organization within NVIDIA. The group works with various other teams within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure and software development workflow needs. As a senior engineer on AI Workflow, you will create and establish tools and software solutions that leverage Large Language Models and agentic AI to automate end to end software engineering workflows and enhance the productivity of engineers across NVIDIA. What you’ll be doing: • Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability • Experience designing, developing, and deploying AI agents to automate software development workflows and processes. • Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR). • Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures. • Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.

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