Leads development of ML algorithms for robot perception, including scene understanding, tracking, segmentation, and multi-modal foundation models using sensor data. Requires deep expertise in deep learning, computer vision, and production ML pipelines, collaborating across autonomy teams.
Develops deep learning models using imitation and reinforcement learning to generate safe, efficient trajectories for autonomous vehicles. Collaborates with perception and planning teams, leveraging large-scale ML infrastructure for production deployment in urban environments.
Develops deep learning models using imitation and reinforcement learning to generate safe, efficient driving trajectories for autonomous vehicles. Collaborates with Perception, Planning, and Simulation teams; requires ML expertise, Python fluency, and transformer experience.
Develops APIs and optimizes large-scale ML model inference using Python, Rust, C++, PyTorch, and CUDA. Benchmarks performance, improves reliability, and implements LLM optimizations on GPU architectures.
Develops and deploys state-of-the-art ML models for AI music generation, owning full research projects from data engineering to evaluation. Requires 5+ years training large generative models like LLMs/diffusion with distributed PyTorch.
Designs and deploys AI-driven agentic systems for retrieval, code generation evaluation, and agent backend architecture. Requires 2+ years AI/ML experience with LLMs, Bachelor's or Master's in CS/AI, and ability to prototype innovative solutions onsite in San Francisco.
Leads development and deployment of ML models for NLP, retrieval, ranking, reasoning, dialog, and code-generation systems. Requires Master's/PhD, production ML experience, deep NLP expertise, Python proficiency, and MLOps knowledge in a fast-paced startup.
Software Engineer optimizes ML model inference performance using techniques like quantization and speculative decoding. Requires backend experience with PyTorch, TensorRT, CUDA, and deep GPU knowledge for LLMs.
Develop and deploy retrieval and search algorithms for OpenAI's API and ChatGPT, collaborating with research teams on production systems for millions of users. Requires experience with ML systems, vector databases, and large-scale search.
Distributed Training Engineer optimizes training throughput for video foundation models, enabling researcher experiments with efficient architectures. Requires strong Python skills, distributed systems expertise, and performance profiling.
Develops and optimizes deep neural networks for Quadric's GPNPU architecture, focusing on algorithmic lowering, graph-based execution, and performance extraction. Requires MS/PhD, 8+ years experience in optimization, ML algorithms, and graphs.
Develops alignment algorithms, data pipelines, and sampling methods to optimize post-training AI models for performance and efficiency. Requires PhD or equivalent, ML expertise including reinforcement learning and transformers, and production code experience.
Leads ML performance optimization for training and inference platforms in autonomous driving, collaborating across teams to enhance efficiency using PyTorch, TensorRT, and profiling tools. Requires strong Python/C++ skills, GPU expertise, and 4+ years in large-scale ML platforms; leads engineering team.
As a Software Engineer specializing in Mapping and Localization, you will design and implement state-of-the-art systems for autonomous vehicles and mobile robots. This role involves building scalable solutions, fusing live data with maps, and continuously improving system performance using data-driven methods.
Develop, deploy, and optimize production-scale ML models using deep learning frameworks like PyTorch/TensorFlow. Requires 5+ years experience, expertise in Python, distributed systems, and focus areas like computer vision or NLP.
Develops, deploys, and optimizes state-of-the-art ML models for production at scale, handling terabyte datasets and neural networks. Requires 8+ years experience, expertise in PyTorch/TensorFlow/Python, and focus in CV/NLP.
Develops and deploys perception algorithms for autonomous driving, focusing on object detection, sensor fusion, localization, and tracking using LiDAR, cameras, and radar. Requires Master's degree and 4+ years non-academic experience in computer vision.
Builds product workflows and agentic systems using language models for research tasks like evidence synthesis and experiment planning. Combines ML fluency with strong software engineering to create reliable, trustworthy AI tools for scientific decision-making.
Develops, trains, deploys, and optimizes deep learning models for production use cases involving large datasets. Requires 1-2 years ML experience, Python proficiency, and familiarity with ML frameworks like TensorFlow or PyTorch.
Leads development of ML algorithms for robot perception, including scene understanding, tracking, segmentation, and multi-modal foundation models using sensor data. Requires deep expertise in deep learning, computer vision, and production ML pipelines, collaborating across autonomy teams.
Develops deep learning models using imitation and reinforcement learning to generate safe, efficient trajectories for autonomous vehicles. Collaborates with perception and planning teams, leveraging large-scale ML infrastructure for production deployment in urban environments.
Develops deep learning models using imitation and reinforcement learning to generate safe, efficient driving trajectories for autonomous vehicles. Collaborates with Perception, Planning, and Simulation teams; requires ML expertise, Python fluency, and transformer experience.
Develops APIs and optimizes large-scale ML model inference using Python, Rust, C++, PyTorch, and CUDA. Benchmarks performance, improves reliability, and implements LLM optimizations on GPU architectures.
Develops and deploys state-of-the-art ML models for AI music generation, owning full research projects from data engineering to evaluation. Requires 5+ years training large generative models like LLMs/diffusion with distributed PyTorch.
Designs and deploys AI-driven agentic systems for retrieval, code generation evaluation, and agent backend architecture. Requires 2+ years AI/ML experience with LLMs, Bachelor's or Master's in CS/AI, and ability to prototype innovative solutions onsite in San Francisco.
Leads development and deployment of ML models for NLP, retrieval, ranking, reasoning, dialog, and code-generation systems. Requires Master's/PhD, production ML experience, deep NLP expertise, Python proficiency, and MLOps knowledge in a fast-paced startup.
Software Engineer optimizes ML model inference performance using techniques like quantization and speculative decoding. Requires backend experience with PyTorch, TensorRT, CUDA, and deep GPU knowledge for LLMs.
Develop and deploy retrieval and search algorithms for OpenAI's API and ChatGPT, collaborating with research teams on production systems for millions of users. Requires experience with ML systems, vector databases, and large-scale search.
Distributed Training Engineer optimizes training throughput for video foundation models, enabling researcher experiments with efficient architectures. Requires strong Python skills, distributed systems expertise, and performance profiling.
Develops and optimizes deep neural networks for Quadric's GPNPU architecture, focusing on algorithmic lowering, graph-based execution, and performance extraction. Requires MS/PhD, 8+ years experience in optimization, ML algorithms, and graphs.
Develops alignment algorithms, data pipelines, and sampling methods to optimize post-training AI models for performance and efficiency. Requires PhD or equivalent, ML expertise including reinforcement learning and transformers, and production code experience.
Leads ML performance optimization for training and inference platforms in autonomous driving, collaborating across teams to enhance efficiency using PyTorch, TensorRT, and profiling tools. Requires strong Python/C++ skills, GPU expertise, and 4+ years in large-scale ML platforms; leads engineering team.
As a Software Engineer specializing in Mapping and Localization, you will design and implement state-of-the-art systems for autonomous vehicles and mobile robots. This role involves building scalable solutions, fusing live data with maps, and continuously improving system performance using data-driven methods.
Develop, deploy, and optimize production-scale ML models using deep learning frameworks like PyTorch/TensorFlow. Requires 5+ years experience, expertise in Python, distributed systems, and focus areas like computer vision or NLP.
Develops, deploys, and optimizes state-of-the-art ML models for production at scale, handling terabyte datasets and neural networks. Requires 8+ years experience, expertise in PyTorch/TensorFlow/Python, and focus in CV/NLP.
Develops and deploys perception algorithms for autonomous driving, focusing on object detection, sensor fusion, localization, and tracking using LiDAR, cameras, and radar. Requires Master's degree and 4+ years non-academic experience in computer vision.
Builds product workflows and agentic systems using language models for research tasks like evidence synthesis and experiment planning. Combines ML fluency with strong software engineering to create reliable, trustworthy AI tools for scientific decision-making.
Develops, trains, deploys, and optimizes deep learning models for production use cases involving large datasets. Requires 1-2 years ML experience, Python proficiency, and familiarity with ML frameworks like TensorFlow or PyTorch.