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NVIDIA is seeking interns for their Deep Learning Computer Architecture teams to work on projects involving GPU/CPU architecture, performance modeling, and parallel programming. Interns will utilize technologies such as C++, CUDA, and deep learning frameworks to solve complex computing challenges.
The Deep Learning Performance Architect will analyze and optimize performance for LLM workloads on NVIDIA's hardware architectures. This role involves developing analytical models and collaborating with software and hardware teams to influence the design of next-generation inference products.
Ph.D. intern designing and implementing novel computer vision and deep learning methods, collaborating with researchers, and transferring results to product groups using Python, C++, CUDA, and frameworks like PyTorch or TensorFlow.
NVIDIA is seeking interns for 12-week roles focused on deep learning applications, algorithms, and framework development. Interns will work on GPU-accelerated computing projects using technologies like CUDA, PyTorch, and TensorFlow.
Principal ML Engineer builds and governs scalable, explainable matching models on AWS SageMaker, setting MLOps standards and ensuring regulatory-grade compliance for a global fintech platform.
Lead a team of 3-6 AI scientists in BlackRock's AI Labs, owning end-to-end delivery of agentic AI workflows and flagship ML initiatives from scoping through production deployment, primarily using Python, LLMs, and AI/ML systems.
Sr Staff Engineer – AI/ML Compiler & Runtime Software Engineer AI SDK Team Location: Pune / Bangalore – India Join the RISC-V Revolution! About GlobalFoundries GlobalFoundries is a leading full-service…
Build and deploy ML models and GenAI tools to turn retail data into actionable insights for suppliers and merchants using Python, GCP, and MLOps.
The Data Scientist Consultant will analyze complex, unstructured data to build and deploy machine learning models and AI-driven solutions for clients. The role focuses on leveraging Python, SQL, and modern AI frameworks like LLMs and RAG patterns to create actionable business insights.
Staff Engineer leading an applied AI team to take models from prototype to production across restaurant operations, digital ordering, and supply chain using Python, ML frameworks (PyTorch/TensorFlow), LLMs, AWS SageMaker/Bedrock, and modern data platforms.
Develops and maintains a government Investment Data Warehouse platform with AI/ML and GenBI capabilities, focusing on data modeling, ETL pipelines, and analytics dashboards using Snowflake, AWS, and React.
The Front-End/Full-Stack Developer will build and maintain analytics dashboards and AI-driven data warehouse solutions for public sector clients. The role focuses on UI/UX design, GenAI integration, and data visualization using technologies like React, Streamlit, Chainlit, and cloud-based AI services.
The Solution Architect will design and advance an Investment Data Warehouse platform, integrating Generative AI, machine learning, and automated decision-making tools within AWS and Snowflake ecosystems. The role involves technical leadership, prompt engineering, and building scalable, secure data pipelines for public sector clients.
The Advanced Analyst II develops and applies advanced machine learning and statistical models to solve complex business problems across retail operations, merchandising, and supply chain. The role involves partnering with stakeholders to deliver data-driven insights using technologies like Python, Azure, and Power BI.
Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients,…
Design, develop, and optimize AI/ML embedded software for HP's commercial PCs and connected devices, deploying machine learning models at the edge using C/C++, Python, and frameworks like PyTorch, TensorFlow, ONNX, and TFLite.
The Embedded AI/ML Developer will design and optimize AI-enabled software for HP's commercial PCs and connected devices, focusing on deploying efficient machine learning models at the edge. The role involves integrating AI inference engines with firmware and system software while collaborating across hardware and data science teams.
Leads the design, development, and operation of full-stack, cloud-native software systems with AI integration for government/cybersecurity products, focusing on scalability, reliability, and automation.
This role involves developing and deploying software tooling for space environment testing, including hardware integration test code and proprietary MBSE software. The position requires proficiency in LabVIEW and Python, with a focus on test automation and hardware driver development.
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.
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