Design and build end-to-end applications that integrate AI-driven physics models into real-world engineering workflows. Collaborate with customers and technical teams to prototype, deploy, and iterate tools that solve complex engineering challenges across industries like aerospace, energy, and semiconductors. Work across the full stack with a focus on backend services, cloud infrastructure, and customer-driven product development.
This role involves developing high-fidelity computational plasma models for semiconductor manufacturing processes such as etching and deposition, integrating them with AI-driven simulation tools. The engineer will work directly with customers on-site, validate models against real-world data, and collaborate with data science and ML teams to deliver actionable engineering solutions. The position emphasizes technical ownership, cross-functional collaboration, and global travel to support customer implementations.
This role involves developing and deploying cutting-edge GenAI solutions for customers, collaborating with product and engineering teams, and presenting at industry conferences. The ideal candidate has extensive experience with GenAI tools and platforms, a passion for collaboration, and a graduate degree in a quantitative field.
This role involves designing and building high-performance backend systems for Databricks' workspace platform, focusing on scalability, reliability, and low-latency operations at massive scale. The engineer will lead technical projects, mentor junior staff, and contribute to core infrastructure innovations within the Delta DML team, which powers the write-path for Delta Lake. Work includes low-level systems debugging, performance optimization, and cross-team collaboration to solve large-scale data challenges.
Design and build scalable data pipeline and orchestration infrastructure to support high-volume data ingestion, processing, and inference workflows for autonomous driving systems. Develop and revamp internal platforms like the Harness system and a new DAG-based orchestration framework. Collaborate with cross-functional teams to ensure reliable, efficient, and developer-friendly data infrastructure at scale.
This role involves developing and optimizing the software stack for Wayve's autonomous driving vehicles, focusing on performance, latency, and system efficiency. You will work closely with multiple teams to identify and resolve bottlenecks, implement profiling tools, and enhance the overall system performance.
This role involves developing and maintaining large-scale web data pipelines for pre-training advanced language models. Responsibilities include processing web corpora, filtering and quality-scoring systems, and collaborating with cross-functional teams to enhance model performance.
As a Machine Learning Intern, you will design, train, and improve cutting-edge AI models, develop novel research ideas, and build training/deployment pipelines. You will work closely with product teams and experienced senior staff, contributing to the development of safe and efficient AI solutions.
Develop and lead the technical architecture for LiDAR and cross-sensor 3D sensing systems, focusing on calibration, synchronisation, and motion compensation across diverse vehicles and environments. Design robust algorithms for sensor alignment and temporal registration using optimisation and state estimation techniques. Provide technical mentorship and drive production-grade deployment of 3D sensing pipelines across Wayve’s autonomous driving platform.
Investigate and resolve complex issues across Wayve's autonomous vehicle stack using data analysis, simulation, and cross-functional collaboration. Focus on root cause analysis, safety, and systemic improvements in a fast-paced AI-driven environment.
This role involves leading complex, cross-functional technical programs across AI, software, robotics, and vehicle systems in a fast-paced environment. The Technical Program Manager will drive project delivery, streamline workflows, and ensure alignment between engineering teams and business goals. The position emphasizes structured execution, risk management, and continuous improvement in the development of autonomous driving technology.
Builds performance analysis tools to optimize AI models across the full stack, from compilers to hardware. Measures, predicts, and advises on latency, throughput, and compute efficiency using profiling data. Works cross-functionally with model, runtime, and hardware teams to drive data-informed performance decisions.
Design and build full-stack applications that streamline model development workflows for autonomous driving systems, including experiment scheduling, evaluation, and on-road testing. Collaborate closely with researchers and engineers to deliver scalable, secure backend services and intuitive web interfaces. Take technical ownership from concept to production, with a focus on reliability, observability, and system integration.
This role involves owning the end-to-end ML compilation pipeline for Wayve's autonomous driving technology, working with NVIDIA TensorRT and Qualcomm QNN. Responsibilities include designing compiler passes, integrating with vendor toolchains, and ensuring accuracy and latency requirements are met across various target platforms.
Develop and optimise calibration and estimation software for autonomous vehicles, focusing on robustness, efficiency, and integration within constrained, hardware-accelerated platforms. Work across sensor data pipelines, state estimation, and fleet-wide observability to enhance vehicle performance and safety.
