Full-Stack Software Engineer, Model Development Platform
As a Full-Stack Software Engineer within Wayve’s Model Development Platform, you will design, build, and operate the applications and services that support the development and testing of our autonomous driving models. These systems help researchers and engineers manage workflows spanning data, model training, experiment scheduling, evaluation, and on-road testing.
You will work across the full technology stack, creating intuitive web applications and the scalable backend services, APIs, and data models that power them. You will take ownership of significant technical areas, from understanding user needs and shaping solutions through to implementation, deployment, observability, and production support.
This is a hands-on engineering role with meaningful technical leadership responsibilities. You will influence technical decisions within the team, establish effective design patterns, contribute to architectural direction, and help engineers make sound technical choices. You will mentor less-experienced engineers through design discussions, code reviews, pairing, and day-to-day collaboration while continuing to write and deliver high-quality production code.
Challenges you will own
Deliver end-to-end platform capabilities
Design and deliver applications that make complex model-development workflows easier to manage—from experiment scheduling and evaluation to on-road testing. Work closely with users to understand their needs, shape pragmatic solutions, and own features from initial design through deployment and continuous improvement.
Build scalable, secure, reliable, and performant services
Build and operate production web applications, APIs, and backend services that perform reliably as usage and complexity grow. Apply sound security practices, identify bottlenecks and failure modes, and use testing, observability, and performance analysis to continuously improve the systems you own.
Shape system design and technical direction
Lead the design of significant features and services, making thoughtful trade-offs between delivery speed, scalability, security, operational simplicity, and maintainability. Contribute to design reviews and establish reusable patterns that help the team build coherent, well-integrated systems.
At the Staff level, you will also guide broader architectural decisions, align approaches across teams, and lead complex, multi-quarter technical initiatives.
Lead through hands-on contribution
Remain actively involved in implementation while helping others make strong technical decisions. Mentor junior and mid-level engineers through design discussions, code reviews, pairing, and practical guidance.
Cross-functional collaboration
Partner closely with Product Management, Research, Operations, Design, and other engineering teams to understand user needs and deliver effective solutions. Communicate technical decisions and trade-offs clearly, build alignment between stakeholders, and ensure platform capabilities work coherently across team and system boundaries.
What we are looking for
Essential
Full-stack engineering – Strong experience designing, building, and operating production web applications across frontend and backend systems. Experience with modern technologies such as React, TypeScript, Python, Flask, or FastAPI—or comparable frameworks and languages.
Production system design – A strong understanding of system design, API design, data modeling, asynchronous workflows, automated testing, and distributed-system fundamentals. Experience building services that are scalable, secure, reliable, observable, and performant.
End-to-end ownership – A track record of taking significant features or services from problem definition and technical design through implementation, deployment, and production operation.
Technical leadership and mentorship – Experience leading technical discussions, influencing engineering decisions, establishing effective design patterns, and supporting other engineers through design reviews, code reviews, pairing, and practical guidance.
Collaborative problem-solving – The ability to work effectively with engineering, product, research, and operational stakeholders, translating complex requirements into practical solutions and communicating technical decisions and trade-offs clearly.
Desirable
Developer or ML Platforms – Experience building internal platforms, developer tools, workflow systems, or applications used by machine-learning researchers and engineers.
ML Operations and Experimentation – Familiarity with model training, evaluation, experiment tracking, artifact management, or related model-development workflows.
Data and Workflow Systems – Experience with data pipelines, distributed job orchestration, event-driven architectures, or large-scale compute platforms.
Platform Observability – Experience defining service-level indicators and objectives and using metrics, logs, traces, and alerting to improve production reliability.
Security and Data Governance – Knowledge of privacy, compliance, access control, auditability, and secure handling of sensitive or large-scale data.
Domain Experience – Previous experience with autonomous systems, robotics, simulation, or another safety-critical domain.
If you are passionate about building thoughtful, high-quality software that helps researchers and engineers develop safe and intelligent autonomous driving technology, we would love to hear from you.
