• Deliver meaningful business impact by designing and building scalable backend systems • Contribute to system design and technical direction • Build high-throughput, low-latency backend systems • Implement fault-tolerant systems with observability layers • Conduct performance analysis identifying bottlenecks • Mentor junior and mid-level engineers • Contribute to shared platform capabilities • Translate operational complexity and regulatory requirements into clear technical recommendations

• We are looking for a Team Leader to join our Technical Platform team for web applications. • We are seeking someone who combines strong technical expertise with leadership skills and can translate product vision and business needs into effective technical solutions. • We build tools and solutions that enable product teams to deliver business value faster, more securely, and more efficiently. We develop web applications using a microfrontend architecture, with a strong focus on quality, scalability, maintainability, and modern technologies.

• Ensuring development tasks are completed according to established technical standards. • Supporting the Product Manager in coordinating team activities in the area of technological solutions. • Collaborating with other teams to design optimal solution architectures. • Ensuring high team efficiency by identifying and mitigating obstacles in the development process. • Monitoring ongoing work and assisting in resolving technical issues. • Supporting team growth through training, mentoring, and regular 1:1 meetings.

• Optimize and deploy neural network models for onboard inference using TensorRT and custom CUDA kernels • Profile and reduce end-to-end latency across the autonomous driving stack—from sensor ingestion to control • Build and maintain the onboard C++ and Rust software infrastructure, including real-time data pipelines, inter-process communication, and hardware abstraction layers • Implement model quantization, pruning, and other optimization techniques to maximize throughput on embedded GPU platforms • Collaborate with ML engineers to ensure models are designed for efficient deployment, and with vehicle systems engineers to meet real-time safety constraints