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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.
Develop, integrate, deploy, and maintain machine learning software solutions for US government missions using Python, Bash, and Linux within a Federal Solutions team.
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.
Ensure SSD firmware quality by developing validation strategies for NVMe features, performing root-cause analysis, and enhancing test automation and CI/CD workflows using Python and AI-assisted tools.
Lead AI/ML technical architect responsible for designing, developing, and deploying AI/ML models and systems for CMS, with hands-on development using Python, TensorFlow/PyTorch, and AWS, while ensuring cybersecurity and data governance compliance.
Build self-service ML platform tooling and golden paths from the ground up, enabling Data Scientists to independently deploy models to production across batch and real-time use cases using Python, PyTorch, TensorFlow, Kubernetes, and MLflow.
Senior Data Scientist building end-to-end production decision systems—forecasting, optimization, pricing, and batch/real-time recommendations—using Python, PyTorch/TensorFlow, and SQL at a lottery and sports-betting company in Toronto.
Job Title: Distribution Ops & Planning Engineer III Location: Knoxville, TN Job Summary and Description: Utilities around the world are transforming their distribution systems to support electrification,…
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.
Build and deploy ML models for personalization, recommendations, and ranking at The Washington Post, using Python, PyTorch/TensorFlow/JAX, and large-scale behavioral data to power intelligent reader discovery experiences.
As a Sr Advanced AI Engineer here at Honeywell Aerospace, you will provide expert-level technical leadership in the design and development of AI algorithms, models, and systems. You will be responsible for acting as…
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.
Research engineer builds and optimizes AI/ML systems for quantitative finance, integrating models into low-latency trading pipelines using Python, C++, and GPU frameworks.
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.
PhD student develops ML models to analyze atmospheric concentrations of plant pathogens using Poleno Jupiter data, atmospheric transport models, and HPC systems like GEFION.
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.
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