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Develops AI-driven predictive models for credit risk and customer behavior using advanced ML techniques, explainability tools, and large-scale data analysis to inform underwriting decisions in a regulated fintech environment.
APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply here, apply internally…
Leads AI and analytics product strategy for Motorola’s Avigilon platform, focusing on computer vision, LLMs, and generative AI to enhance physical security systems. Owns end-to-end product vision, technical trade-offs, and cross-functional execution for high-scale AI capabilities in cloud/edge environments.
Develops and optimizes ML models for 3D reconstruction, human pose estimation, and computer vision tasks using Python, PyTorch/TensorFlow, and 3D data formats. Integrates algorithms into pipelines and collaborates with cross-functional teams to advance intelligent systems for automotive, aerospace, and defense industries.
Develops fast-running surrogate models and hybrid digital twins to enable predictive maintenance, real-time analytics, and automated design optimization for HVAC systems using physics-based simulations and machine learning.
Build and maintain scalable data pipelines on Databricks using PySpark, Delta Lake, and cloud services to transform raw data into insights for analytics and AI workloads.
Owns ML products end-to-end, from problem definition to production deployment and impact measurement, focusing on canonical data, entity resolution, retrieval/ranking, and applied LLMs for career transition tools.
Senior ML Engineer builds and deploys enterprise-scale AI systems for Disney’s guest experiences, focusing on LLMs, agentic workflows, and MLOps pipelines.
Builds and deploys ML models to analyze store equipment telemetry data, using Python, PySpark, and Azure cloud tools to drive operational insights and efficiency.
Site: Massachusetts Eye and Ear Infirmary Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our…
The AI Engineer will design, develop, and deploy Generative AI solutions, including chatbots, copilots, and RAG-based applications using Azure, Python, and various AI frameworks. The role involves integrating AI services into enterprise applications and maintaining MLOps workflows.
Graduate-level co-op Data Scientist at Philips supporting the development, analysis, and validation of machine-learning workflows for clinical imaging software in the Image Guided Therapy Devices group.
The Senior Deep Learning Engineer will design and build evaluation infrastructure for NVIDIA's frontier AI models, including LLMs and agentic systems. This role involves developing novel benchmarking methodologies and collaborating with research teams to guide model releases using large-scale GPU clusters.
The Senior Technical Program Manager will lead large-scale engineering programs for NVIDIA's DGX Cloud, focusing on AI capacity enablement, infrastructure bring-up, and cross-functional process management. The role involves managing roadmaps, driving execution across engineering teams, and communicating program status to executive leadership.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping…
Designs and oversees AI infrastructure architectures (K8s-based) for NVIDIA, focusing on performance, scalability, and integration of AI workloads across hardware/software ecosystems.
Intern on NVIDIA's Deep Learning Software QA team building and maintaining test automation infrastructure for the AI software stack across GPU computing platforms, using Python, C++, and Linux.
Develops test automation tools and AI-driven solutions for NVIDIA’s software distributions across desktop, mobile, and embedded platforms, focusing on SDKs, developer tools, and deep learning packages.
Senior MLOps Engineer on NVIDIA's DSX Enablement team, building and deploying AI solutions on NeoCloud/NCP platforms with focus on distributed training, inference optimization, and MLOps pipelines using Python, C++/Go/Rust, Kubernetes, and the NVIDIA stack.
QA intern on the Spark RAPIDS team responsible for GPU software testing, test automation infrastructure development, and web services for NVIDIA's deep learning frameworks and GPU workloads.
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