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A Machine Learning Research Engineer working on LLM training, inference optimization, and large-scale distributed compute for Tenstorrent's custom AI accelerators, using Python, PyTorch, and techniques like speculative decoding and distributed training.
Build and scale LLM infrastructure, RAG systems, and agentic AI for enterprise search and assistants, working with Python/Go/Java.
Build and deploy ML models to optimize driver assistance services using Python and AWS SageMaker, collaborating with cross-functional teams to improve operations and customer satisfaction.
Machine Learning Engineer at Capable Labs (San Francisco, on-site) building ML systems that remove bottlenecks in drug discovery and development. Day-to-day involves fine-tuning biomolecular models (ESM, AlphaFold-family, RFdiffusion, ProteinMPNN), building tools for scientists, and connecting model predictions to wet-lab results.
Research scientist at an MIT-born, venture-backed startup building an AI copilot for design and manufacturing. You'll develop geometry processing and simulation algorithms, build services for 2D/3D CAD/CAE/CAM data, create datasets and rendering modules, and optimize ML post-training workflows. Core stack is Python and machine learning.
Within Monetization (Ads), the Experimentation team is responsible for Measurement Statistics, Measurement Correctness, and Measurement Infrastructure, which underpins model-based experimentation. Every change to our…
Develops and optimizes large-scale vision-language models for autonomous vehicle perception, training pipelines on multimodal sensor data to improve real-world driving decisions.
Develops and deploys machine learning models for autonomous vehicle prediction and planning, using deep learning frameworks to improve navigation safety and efficiency.
Develops and optimizes machine learning systems for autonomous driving, focusing on runtime performance and efficiency across cloud and vehicle platforms using deep learning frameworks and compiler tools.
Develops ultra-realistic simulations for autonomous driving using generative AI and diffusion models to test and train Waymo’s self-driving systems.
Develops ultra-realistic simulation environments for autonomous driving using machine learning, focusing on generative AI and foundation models to enhance the Waymo Driver's performance.
Develops machine learning models for autonomous vehicle perception, including sensor fusion and spatial-temporal representation learning, using large-scale real-world driving data.
Research Scientist designs and builds deep-learning models for autonomous-vehicle planning and prediction, turning real-world driving challenges into robust ML systems and publishing findings.
Builds and improves autonomous-vehicle simulations using deep learning and large foundation models to train and evaluate Waymo’s self-driving software in London.
Designs and optimizes large-scale machine learning pipelines for vision-language models to improve autonomous vehicle perception, using Python and deep learning frameworks.
Senior Machine Learning Engineer at Waymo to transition perception tasks from algorithms to ML, optimize sensor data pipelines, and integrate systems for autonomous driving using C++, Python, and computer vision.
Senior ML Engineer builds and optimizes high-performance inference engines for autonomous vehicle ML models, balancing real-time onboard constraints with offboard data center demands using frameworks like JAX, XLA, and CUDA.
Senior engineer building and scaling AI/ML infrastructure for ultra-realistic autonomous-driving simulations using multi-billion-parameter foundation models and distributed training.
Leads a small team optimizing machine learning model performance for autonomous driving software, focusing on C++/Python code and ML compiler tools.
Senior engineer building AI/ML infrastructure for autonomous-driving simulations, scaling multi-billion-parameter foundation models on large distributed systems.
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