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Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the…
Builds and optimizes ML infrastructure for Nuro’s autonomous vehicle fleet, focusing on model compression, deployment, and performance improvements (e.g., quantization, distillation) to enhance real-world autonomy.
Builds and optimizes ML infrastructure for Nuro’s autonomous vehicle fleet, focusing on model pipelines, compilers (e.g., FTL), and deployment of optimized models for safe on-road navigation.
Develop synthetic sensor simulation models and algorithms using ML techniques like NeRF and Gaussian splatting to generate photorealistic images and realistic lidar/radar data for autonomous vehicles. Work with Python, PyTorch/TensorFlow/Jax, and collaborate across autonomy and infrastructure teams to improve sensor data realism and utility.
Lead the Behavior & Planning team at Nuro to design, train, and deploy ML models for autonomous driving, turning real-world data into safe, natural driving behavior across robotaxis, logistics fleets, and personal vehicles.
Software Engineer on the ML Developer Experience team building developer tooling, SDKs, CLIs, APIs, and platform services for the Anyscale/Ray distributed computing platform, spanning cloud infrastructure to the Ray runtime.
Builds and deploys AI/ML models and applications to automate decisions and insights for a reverse-mortgage fintech, using Python, TensorFlow/PyTorch, and cloud MLOps.
Senior Data Scientist analyzing energy market operations at an RTO, building predictive analytics, dashboards, and automated alerts using Python/R, ML frameworks, and cloud platforms to support grid reliability decisions.
Build and deploy AI systems for public safety, including computer vision, speech recognition, NLP, and generative AI, across cloud and edge devices.
Senior Software Engineer at Attentive builds scalable backend or full-stack systems for onsite customer growth features, using Java/Kotlin, TypeScript, React, and AWS microservices to drive personalized marketing experiences.
Senior Data Scientist at an AI services firm, working across the full data lifecycle—cleaning, analyzing, and building ML models using Python, SQL, Databricks, and cloud platforms (Azure/AWS), with regular client-facing onsite work in DFW.
Builds mid-training strategies for large multimodal AI models to improve reasoning, planning, and tool-use capabilities at scale.
Build post-training strategies (RL-based) to train coding and agentic AI models, including reward modeling, simulation environments, and evaluation frameworks.
About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and…
Lead the design, training, and on-device deployment of audio ML models for wake-word detection, voice enhancement, and speech processing in Hark’s AI-powered hardware products.
Build and deploy ML systems that reconstruct 3D lane lines and maps from noisy sensor data (cameras, LiDAR, radar, GPS/IMU) to power autonomous truck perception and HD mapping.
Build and deploy ML models for 3D scene reconstruction, lane detection, and HD map creation using LiDAR/camera data to auto-generate high-quality annotations for autonomous trucks.
The Machine Learning Engineer will provide MLOps support for autonomous trucking model development, including debugging pipelines, maintaining infrastructure, and collaborating with engineering teams. The role focuses on ensuring reliable model deployment using Python, PyTorch, and various MLOps orchestration tools.
Lead AI/ML Engineer defining architecture and strategy for enterprise AI/ML pipelines, mentoring teams, and integrating LLMs and Generative AI into production using Python, cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and MLOps tooling.
Design, build, and deploy ML models for forecasting, supply-chain optimization, and anomaly detection using Python and SQL, then communicate insights via dashboards.
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