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Build and fine-tune LLMs, craft AI agents, and deploy ML models using Python, PyTorch/TensorFlow, and LangChain/LlamaIndex in a remote R&D team.
Design and evangelize AI/ML solutions for healthcare clients, building predictive models, NLP workflows, and MLOps pipelines while ensuring compliance and scalability.
About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment,…
The Staff Machine Learning Engineer will lead the development of safety-critical, end-to-end driving models for autonomous vehicles using large-scale data and transformer-based architectures. This role involves setting technical strategy, conducting research, and collaborating across teams to improve model robustness and performance in real-world driving scenarios.
Build and refine data pipelines and evaluation frameworks for autonomous-driving foundation models, curating rare driving events and measuring model progress to scale safe, generalizable AI for vehicles.
Senior ML engineer optimizes PyTorch models for edge deployment, iterating from training to production-ready releases under tight latency and memory constraints for autonomous-vehicle systems.
Develops 3D foundation models and world models for autonomous driving systems, focusing on geometric vision, multi-view geometry, and sensor fusion (LiDAR, radar, camera) to enable vehicles to perceive and navigate complex environments.
Build and refine computer vision models to measure autonomous driving performance offline, adapting foundation models for scene understanding and benchmarking accuracy across conditions.
Lead a team building offline scene-understanding models for autonomous vehicles, turning on-vehicle models into robust validation systems that predict counterfactual outcomes and assess AV2.0 driver behavior.
Leads a data science team to analyze real/simulated driving data, drive engineering progress, and scale operations for Wayve’s AI-powered autonomous vehicle tech.
Leads development of AI-driven emergency trajectory models for autonomous vehicles, focusing on evasive maneuvers and collision avoidance. Combines ML research, system integration, and safety validation to deploy high-consequence models in production.
Software Engineer on Wayve's AI Libraries team building Python libraries, tools, and platforms that enable ML engineers to train, evaluate, and scale autonomous driving models across large GPU clusters.
Wayve is seeking a Machine Learning Engineer to develop efficient, interactive generative world models for autonomous driving simulation. You will focus on optimizing model performance and inference latency to enable closed-loop training and evaluation of driving systems.
The Machine Learning Engineer will build and scale generative world models to create synthetic data for autonomous driving systems. This role involves collaborating with researchers to post-train models, manage large-scale GPU inference pipelines, and integrate synthetic data into the training stack for driving models.
The Staff Machine Learning Engineer (Ops) will oversee the end-to-end model development and release lifecycle for autonomous driving AI. This role involves optimizing ML delivery pipelines, enforcing quality gates, and collaborating with platform and CI/CD teams to ensure robust model deployment.
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