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The Senior Machine Learning Engineer will develop and implement autonomous driving algorithms and scalable ML systems for Uber's AV Labs. The role focuses on leveraging large-scale real-world driving data using Python, PyTorch, and C++ to advance physical AI technologies.
Build and maintain scalable MLOps platforms and pipelines supporting drug discovery at Amgen, using Python, AWS/Databricks, and AI/ML frameworks to productionize models from classical ML to LLMs.
Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and…
Staff Software Engineer on Google Cloud's AI/ML team, leading design and optimization of large-scale ML infrastructure, model deployment, and data processing strategies for Vertex AI and related platforms.
Research and develop machine learning models for autonomous vehicle behavior planning and prediction, deploying solutions on real-world self-driving vehicles using Python and C++.
Research and develop generative AI models (diffusion, flow-matching) for autonomous vehicle planning, integrating foundation models and reinforcement learning to improve decision-making and real-world deployment.
Develops advanced generative AI models (e.g., diffusion, flow matching) for autonomous vehicle planning, optimizing for safety, efficiency, and real-world deployment. Focuses on end-to-end model lifecycle, including research, productization, and collaboration with engineering teams.
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.
Senior Software Engineer at Nuro developing machine learning models for autonomous driving, focusing on perception, sensor fusion, and real-time deployment in C++ and Python.
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.
Senior Computer Vision Engineer building real-time detection, classification, and tracking systems at the intersection of Computer Vision, Software Engineering, and Edge AI for a scaling Australian tech company.
Build the evaluation/judgement layer for AI agent trajectories at Moveworks/ServiceNow — designing LLM judges, rubrics, calibration loops, and process reward models so that evaluation scores can be used as training signals. Core tech: LLMs, Python, fine-tuning, reward modeling.
Senior Software Engineer on Google Maps Ads ML, building and improving ML models for ad retrieval, pre/post-click quality, and pricing using Python or C++ with strong backend engineering skills.
On our Corporate Systems AI team you’ll develop, customize, and integrate opportunities where AI can enhance operational efficiencies for in-house and third-party applications utilized across teams that span Human…
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.
Build and scale Torc Sim, a simulation platform that replays and evaluates autonomy models against real and synthetic driving data, enabling teams to debug and improve ML models for self-driving trucks.
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.
Develops a C++ SDK/framework for composing and running autonomous-truck software on embedded Nvidia devices, focusing on performance, safety, and resource constraints.
Build and deploy ML models for autonomous trucking, focusing on data pipelines, deep learning, and production deployment while exploring cutting-edge AI initiatives.
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