8 Gpu Acceleration Jobs

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions. Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems. Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency. Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications. Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies. Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms. What We Need To See Master's or Ph.D. in Computer Science, AI, or a related field 5+ years of hands-on experience with LLM training, deployment, and production optimization Deep understanding of language models like GPT-3, BERT, and experience with RAG Proficient in PyTorch, TensorFlow, and Hugging Face Transformers Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware Experience presenting to clients and leading cross-functional collaboration Strong communication skillsable to clearly explain technical details to diverse audiences Ways To Stand Out From The Crowd Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters Proficiency with Docker, Kubernetes, and GPU cluster management Proven ability to optimize LLM inference for speed, memory, and cost Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next. We are an equal opportunity employer and committed to diversity in our workforce.

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with deep expertise in training Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) workflows. As a key member of our AI Solutions team, you'll drive innovation and impact in real-world deployments of cutting-edge generative AI technology. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate with customers to understand business problems and translate them into tailored LLM-based solutions. Design and lead workshops and technical sessions to define, optimize, and deploy RAG-based and LLM-powered systems. Train and fine-tune state-of-the-art LLMs on NVIDIA platforms, optimizing for performance, cost, and efficiency. Deploy and integrate LLMs and RAG workflows in cloud and on-premise environments, enabling real-world applications. Work closely with NVIDIA engineering and product teams, influencing the evolution of generative AI tools and technologies. Build and share best practices for model training, deployment, and performance optimization using NVIDIA GPUs and AI platforms. What We Need To See Master's or Ph.D. in Computer Science, AI, or a related field 5+ years of hands-on experience with LLM training, deployment, and production optimization Deep understanding of language models like GPT-3, BERT, and experience with RAG Proficient in PyTorch, TensorFlow, and Hugging Face Transformers Familiar with GPU acceleration, distributed computing, and inference tuning on NVIDIA hardware Experience presenting to clients and leading cross-functional collaboration Strong communication skillsable to clearly explain technical details to diverse audiences Ways To Stand Out From The Crowd Experience deploying LLMs in cloud (AWS, Azure, GCP) and on-prem clusters Proficiency with Docker, Kubernetes, and GPU cluster management Proven ability to optimize LLM inference for speed, memory, and cost Hands-on experience with NVIDIA GPU technologies, profiling, and distributed model execution If you're passionate about the future of AI and want to help define how organizations use LLMs at scale, we want to hear from you. NVIDIA is widely considered one of the most desirable employers in techjoin us in shaping what's next. We are an equal opportunity employer and committed to diversity in our workforce.

As a Machine Learning Intern at our company located in Surat, you will be involved in the annotation, building, training, evaluation, and fine-tuning of machine learning and deep learning models across various use cases. Your responsibilities will include implementing data pipelines for preprocessing, augmentation, and transformation of structured and unstructured datasets. Additionally, you will be expected to perform exploratory data analysis (EDA), feature engineering, and data visualization. Furthermore, you will work on computer vision and image/video processing tasks using industry-standard frameworks. Your role will also involve utilizing GPU acceleration (CUDA, cuDNN, TensorRT) for training and optimizing deep learning models. You will be responsible for deploying models on-premise and in cloud environments using containerization (Docker) and orchestration (Kubernetes). Collaboration is a key aspect of this role, as you will be working in an agile development team, contributing to architecture, experimentation, and testing workflows. This position is ideal for individuals with a background in BE (CSE/IT)/B.TECH(CSE/IT)/MCA/ME(CSE/IT)/M.SC/M.TECH(CSE/IT) who are looking to kickstart their career in machine learning and deep learning. This is a paid internship opportunity suitable for fresher/internship candidates who are seeking a full-time role.,

As an AI Computer Vision Engineer with 4+ years of experience, you will be responsible for developing and training computer vision models for various tasks such as object detection, image classification, and face recognition. You will optimize models for performance on edge devices and apply data augmentation techniques to image/video datasets. Additionally, you will need proficiency in Large Language Models and a strong understanding of statistical analysis and machine learning algorithms. Your role will involve hands-on implementation of machine learning algorithms like linear regression, logistic regression, decision trees, and clustering algorithms. Understanding image processing concepts and experience in model optimization, quantization, or deploying to edge devices will be essential. You should have strong programming skills in Python (or C++) and expertise in implementing and optimizing machine learning pipelines for seamless integration into production systems. Experience with real-time computer vision applications, OpenCV, NumPy, PyTorch/TensorFlow, and computer vision models like YOLOv5, Mask R-CNN will be beneficial. Engaging with multiple teams, contributing to key decisions, and providing solutions that apply across multiple teams are expected from you. You will lead the implementation of large language models in AI applications and research cutting-edge AI techniques to enhance system performance. Contribution to the development and deployment of AI solutions across various domains is also part of your responsibilities. In terms of requirements, you should design, develop, and deploy ML models for OCR-based text extraction, table and line-item detection, and named entity recognition. Evaluating and integrating third-party OCR tools, developing pre-processing and post-processing pipelines for image/text data, and familiarity with video analytics platforms are necessary skills. Experience with MLOps tools, academic CV research, and knowledge of GPU acceleration or hardware integration will be advantageous for this role.,

Job Description Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area As a Quantitative Modeler within the Quantitative Research team at J.P. Morgan, you will play a pivotal role in shaping our firm&aposs future and will provide effective, timely, and independent assessments of our booking models and contribute to the development of alternative benchmarking models. Join our dynamic and growing Quantitative Research team at J.P. Morgan as a Quantitative Modeler. This role offers the chance to shape our firm&aposs future by providing independent assessments of our booking models and developing alternative benchmarking models. You&aposll have the opportunity to leverage your experience in designing independent valuation applications, making a significant impact on our team. Our global team is a leader in financial engineering, data analytics, statistical modeling, and portfolio management, partnering with various stakeholders across all products and regions. Job Responsibilities Define the architecture for a state-of-the-art model calibration and independent valuation application that is modular, scalable and robust Integrate and develop mathematical models for the calculation of pricing adjustments, model limitation provisions, model parameter uncertainty reserves and other regulatory calculations like prudential valuation adjustments and CCAR stresses Drive initiatives for increased automation and digitization across the model space, including inventories of models, products, limitations and adjustments Design and implement data pipelines for the ingestion, processing and storage of independent datasets used for model calibration and build analytics to remediate model limitations identified by the model validation team to better manage the model risk appetite of the firm Optimize the application for high performance utilizing distributed computing, cloud-based solutions, or GPU acceleration where possible Design and develop software frameworks for analytics and their delivery to downstream systems and application Required Qualifications, Capabilities And Skills You demonstrate quantitative and problem-solving skills as well as research skills You demonstrate proficiency in software design patterns, code design and programming skills, with primary focus on Python and C++; You have practical experience with code performance optimization, debugging and reverse engineering You understand advanced mathematics arising in financial modeling, such as probability theory, stochastic calculus, statistics etc. You have hands-on experience with data analytics, including working with large data sets and tools for data analysis and visualization. You have excellent verbal and written communication and team skills in a multi-location set-up Preferred Qualifications, Capabilities And Skills Advanced degree (PhD, MSc or equivalent) in Computer Science, Engineering, Mathematics, Physics, etc. Markets experience and familiarity with general trading concepts and terminology Knowledge of options pricing theory, trading algorithms, financial regulations, stochastic process, partial differential equations and numerical analysis Knowledge of financial products, their payoff functions and models Familiarity with full-stack software development ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the worlds most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants and employees religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team The Corporate & Investment Bank is a global leader across investment banking, wholesale payments, markets and securities services. The worlds most important corporations, governments and institutions entrust us with their business in more than 100 countries. We provide strategic advice, raise capital, manage risk and extend liquidity in markets around the world. Show more Show less

Qualcomm India Private Limited is looking for a highly skilled and experienced MLOps Engineer to join their team and contribute to the development and maintenance of their ML platform both on premises and AWS Cloud. As a MLOps Engineer, your responsibility will include architecting, deploying, and optimizing the ML & Data platform supporting the training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial for ensuring the smooth operation and scalability of the ML infrastructure. You will collaborate with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of the ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Your responsibilities will include architecting, developing, and maintaining the ML platform, designing and implementing scalable infrastructure solutions for NVIDIA clusters on premises and AWS Cloud, collaborating with data scientists and software engineers to define requirements, optimizing platform performance and scalability, monitoring system performance, implementing CI/CD pipelines, maintaining monitoring stack using Prometheus and Grafana, managing AWS services, implementing logging and monitoring solutions, staying updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proposing enhancements to the ML platform. Qualcomm is looking for candidates with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, proven experience as an MLOps Engineer or similar role with a focus on large-scale ML and/or Data infrastructure and GPU clusters, strong expertise in configuring and optimizing NVIDIA DGX clusters, proficiency in using the Kubernetes platform and related technologies, solid programming skills in languages like Python, Go, experience with relevant ML frameworks, in-depth understanding of distributed computing and GPU acceleration techniques, familiarity with containerization technologies and orchestration tools, experience with CI/CD pipelines and automation tools for ML workflows, experience with AWS services and monitoring tools, strong problem-solving skills, excellent communication, and collaboration skills. Qualcomm is an equal opportunity employer and is committed to providing reasonable accommodations to support individuals with disabilities during the hiring process. If you are interested in this role or require more information, please contact Qualcomm Careers.,

Location: [BANGALORE] Experience: 8+ years Role Summary We are looking for a highly skilled Software Architect to lead the design and architecture of a Windows-based medical software application. The application will process image and point cloud data to generate and manipulate 3D CAD visualizations, enabling advanced interaction capabilities for end users in clinical settings. Key Responsibilities- 1. Lead end-to-end architecture design for a high-performance medical imaging software application. 2. Architect modules for image processing, point cloud registration, and 3D CAD model generation. 3. Define software components, data flow, and modular architecture for scalability and maintainability. 4. Select and integrate tools, frameworks, and libraries for 3D rendering, computer vision, and data handling. 5. Collaborate with UI/UX, development, and testing teams to ensure consistency across components. 6. Ensure compliance with healthcare software standards (e.g., HIPAA, FDA 510(k), ISO 13485, IEC 62304). Required Skills & Tools- 1. Strong expertise in software design patterns, modular system architecture, and MVC/MVVM. 2. Expertise in C++, C#/.NET, and Python (for scripting/data processing). 3. Proficient in Windows desktop application development (Win32, WPF, UWP). 4. Experience with 3D Visualization Libraries: VTK, Open Inventor, OpenGL/DirectX, or Assimp. 5. Experience with Point Cloud Processing: PCL (Point Cloud Library), Open3D. 6. Familiar with CAD toolkits/APIs such as Open CASCADE, Siemens Parasolid, or Autodesk Forge. 7. Knowledge of camera interface protocols, image formats, and video data streams. 8. Familiarity with DICOM, medical image formats, and 3D reconstruction techniques. 9. Strong understanding of multithreading, GPU acceleration, and real-time data streaming.

Develop and optimize HPC applications and algorithms using CUDA, MPI, OpenMP on Azure and cluster systems. Support scientific teams by modernizing codebases and enabling GPU acceleration. Required Candidate profile Software engineer with 5+ years in HPC programming, scientific code optimization, GPU computing, and collaboration with research teams.