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The AQE Research Analyst will develop quantitative investment strategies by applying machine learning, NLP, and data science techniques to large datasets. The role involves back-testing alpha signals and collaborating with global teams to build scalable investment solutions.
Design, build, and deploy AI/ML solutions on AWS for energy-sector clients, turning data into business impact while leading teams and advising customers.
The Machine Learning Engineer will design, build, and deploy production-grade machine learning and GenAI systems, including LLM integration and RAG pipelines. The role involves working across the full ML lifecycle, from data exploration and model training to MLOps and cloud-based deployment on AWS.
The Lead Research Engineer will develop and implement AI, machine learning, and computer vision algorithms to support visual inspection and diagnostics for energy equipment. The role involves collaborating with cross-functional teams to build scalable solutions using Python, PyTorch, and TensorFlow.
The Research Scientist will develop advanced AI and computer vision algorithms to support visual inspection, diagnostics, and prognostics for GE Vernova's energy equipment. The role involves building prototypes, analyzing large datasets, and collaborating with cross-functional teams to drive industrial innovation.
The Technical SETA SME provides expert support for AI security research programs, overseeing the lifecycle from development to transition. The role requires deep expertise in AI/ML security, adversarial threats, and federal governance frameworks while working on-site in Bethesda, MD.
Design and implement compiler transformations for CUDA Tile, an MLIR-based tile programming model, optimizing GPU kernel performance across NVIDIA architectures using C/C++.
The University of Kansas Medical Center is seeking a tenure-track faculty member to conduct research in statistical AI and biomedical data science while teaching and mentoring graduate students. The role involves developing external funding and collaborating with interdisciplinary research centers on projects related to cancer, precision medicine, and clinical trials.
The Machine Learning Engineer will develop and deploy generative AI models, including diffusion and multimodal LLMs, to power creative features across Snapchat and wearable devices. The role involves building full-stack generative pipelines for image, video, and audio, with a focus on both server-side and on-device inference.
Lead the development of advanced AI/ML systems powering next-generation journalism at The Washington Post, focusing on AI-powered search, retrieval, ranking, content understanding, and generative AI reader experiences using Python, PyTorch/TensorFlow/JAX, and cloud infrastructure.
Senior Machine Learning Scientist working on Protein ML for AI-driven drug discovery at Genentech, developing AI solutions to advance healthcare and create new treatments.
Build and run machine learning models that turn high-volume security telemetry into accurate, low-noise detections for SoFi’s SOC and fraud teams, using Python, SQL, Spark, and cloud data platforms.
Research engineer builds and deploys deep-learning models for financial markets, using Python/C++/CUDA and PyTorch/JAX to optimize HPC pipelines and integrate low-latency systems.
Senior Staff Software Engineer on LinkedIn's AI Infrastructure team, responsible for designing and optimizing large-scale distributed training and serving systems for AI models (e.g., LLMs, recommendation engines), using frameworks like PyTorch, TensorFlow, Horovod, and DeepSpeed to scale up to hundreds of billions of parameters and high-throughput GPU inference.
Remote AI Engineer leading end-to-end AI/ML projects with Python, deep learning, NLP/LLMs, and MLOps, requiring active IRS MBI clearance.
Forward Deployed Engineer owning end-to-end onboarding and production deployment of an AI data curation platform for strategic enterprise accounts, using Python, AWS, Kubernetes, and distributed systems across cloud environments.
Research intern applies deep learning to financial markets, building and optimizing ML models in Python/C++/CUDA and deploying them into low-latency trading systems.
Remote Data Scientist focused on building machine learning models to detect financial crime risk and security threats, using big data frameworks, graph/NoSQL databases, and deep learning techniques.
Build and optimize cutting-edge generative AI models for image generation and multimodal applications using AMD’s GPUs, collaborating with researchers and engineers to push visual computing boundaries.
Principal ML Engineer builds 3D foundation models for autonomous driving, focusing on geometric vision, neural rendering, and world modeling using large-scale sensor data and PyTorch/C++.
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