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The ML Engineer will design, build, and deploy deep‑learning driving models and related data pipelines, evaluation tools, and production systems for autonomous vehicles, collaborating with AI, simulation, and robotics teams. Core technologies include Python, PyTorch, C++, CUDA, and real‑time robotics.
Lead a new Application Engineering team to develop and deploy autonomous driving features for the US market, overseeing robotics, machine learning, and systems integration while hiring, mentoring, and collaborating with OEM partners.
Lead a Japan-based team to localize and develop autonomous driving features, overseeing robotics, machine learning, and systems integration while collaborating with OEMs and global engineering teams.
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.
The Staff Machine Learning Engineer builds and fine‑tunes computer‑vision and scene‑understanding models for offline performance measurement of autonomous vehicles, leveraging Python, PyTorch, transformer‑based vision models and large foundation models, and benchmarks their accuracy across platforms and conditions.
Train, debug, and ship computer vision and 3D perception models powering Wayve's ADAS driver-assistance products, working across the full ML lifecycle — building scalable data pipelines (incl. auto-labelling), training, evaluating, and iterating on detection, segmentation, and tracking. Involves both on-car latency-constrained models and offline large-scale data generation using CV/deep learning,
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 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.
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.
Senior ML Engineer building and operating large‑scale search and indexing systems for Wayve’s multimodal video data, developing vector‑based retrieval, APIs, and evaluation pipelines using Python and tools like FAISS/LanceDB.
Lead the design, training, and productionization of ML models powering feed recommendations and buyer personalization at Whatnot's live shopping marketplace. Day-to-day spans end-to-end ML project ownership (feature engineering, training, deployment, experimentation) plus backend work with Python, SQL, PyTorch, and XGBoost.
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Are you looking to have an impact on the daily life of millions of entrepreneurs in France (and tomorrow in Europe)? Are you looking for a work environment that values trust, proactivity, and autonomy? Are our…
Senior AI/ML Engineer building LLM, RAG, agentic-AI and computer-vision services for the RETAILIQA retail quality-control platform — from architecture and PoCs through to production. Stack: Python, FastAPI, LangGraph, vLLM, pgvector/Milvus; flexible schedule, remote-friendly, based in Yekaterinburg.
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