10 Nvidia Jobs

Job Title: Lead Solutions Architect AI Infrastructure & Private Cloud Job Summary: We are seeking a highly skilled Lead Solutions Architect with deep expertise in AI/ML infrastructure, HPC, and container platforms to lead the design and delivery of enterprise-grade AI solutions. You will architect and optimize private cloud environments powered by NVIDIA AI Enterprise and GreenLake technologies, enabling scalable, secure, and high-performance AI workloads. Key Responsibilities: 1. Leadership & Strategy Lead solution design and delivery of AI/HPC platforms (OpenShift, Rancher, etc.) aligned with business goals and NVIDIA AI Factory principles. Ensure delivery assurance, stakeholder alignment, and risk management across the project lifecycle. 2. Architecture & Integration Architect containerized and HPC workloads using platforms like Red Hat OpenShift, SUSE Rancher, Slurm, and PBS Pro. Integrate NVIDIA AI Enterprise and open-source ML tools into broader software ecosystems. 3. Technical Engagements Lead RFP/RFI responses, customer consultations, and PoCs to validate performance and integration. Recommend optimal infrastructure configurations using reference architectures from clients and partners. 4. Innovation & Enablement Stay updated on trends across HPC, Kubernetes, hybrid cloud, and security to drive innovation. Mentor consultants and promote internal knowledge-sharing. 5. Customer-Centric Delivery Act as a trusted advisor, translating complex technical concepts into business value. Collaborate with infrastructure, DevOps, and data science teams for seamless delivery. Required Skills & Experience: AI Infrastructure & HPC: Proficiency in workload schedulers (Slurm, PBS Pro), cluster management tools (HPCM, Base Command Manager), and high-speed networking (InfiniBand, Ethernet). Containers & Orchestration: Hands-on experience with Docker, Podman, Singularity; expertise in Kubernetes, OpenShift, Rancher. Deep knowledge of NVIDIA GPU Operator, DCGM, and GPU optimization. Operating Systems & Virtualization: Advanced Linux admin skills (RHEL, SLES, Ubuntu) and experience with virtualization (KVM, OpenShift Virtualization). Cloud, DevOps & MLOps: Experience with hybrid cloud environments, CI/CD, IaC, and integrating ML frameworks into production workflows. Understanding of cloud-native security, observability, and compliance. Networking & Protocols: Strong grasp of networking (TCP/IP, DNS, routing) and protocols like S3, NFS, SMB for hybrid data workflows. Programming & Automation: Scripting experience in Python, Bash, and automation of infrastructure/ML pipelines. Soft Skills & Leadership: Strong communication, project leadership, and stakeholder management skills. Ability to align technical solutions with enterprise business objectives. Qualifications: Bachelor’s/Master’s in Computer Science or related field. 8–10 years of experience in AI/ML, HPC, and container-based solutions. Preferred certifications: RHCSA, RHCE, CKA, CKAD, CKS, NVIDIA Certified – AI Infrastructure & Ops.

Regional lead for AI Infrastructure Sales focused across industries and segments. Global role based in territory with international travel required. Be an integral part of the AI revolution. Oracle is experiencing unprecedented growth through delivering market-leading AI Infrastructure we are looking for exceptional individuals to join our team as we continue to scale the business. Qualifications 5+ years of Sales or relevant experience, preferably with 1-2 years in the AI Infrastructure space. Track record of selling complex solutions and an understanding of infrastructure deployments including lead times, margin analysis, and market demand. Technical depth is strongly preferred. Understanding of the Partner Ecosystem including but not limited to NVIDIA, AMD, Dell, Lenovo, Supermicro, Deloitte, Accenture, etc. Proven success selling to the in-region markets and creating a new business from the ground up. Strong experience in pipeline generation, deal management, closing, and working across departments. Knowledge of the local AI Community and government space and a desire to build a new AI ecosystem with OCI at the center. Employer Description As a world leader in cloud solutions, Oracle uses tomorrow's technology to tackle today's challenges. We've partnered with industry-leaders in almost every sector-and continue to thrive after 40+ years of change by operating with integrity. Primary job duty is to sell AI cloud infrastructure and related services in the region across multiple verticals, segments, and government entities. Identifies, qualifies, and closes new opportunities. Manages accounts through the entire sales process from business development prospecting and specifications through contract negotiations, signing, and post-sales support. Leverages the Oracle sales model to maximize revenue growth and increase local market share. Career Level - IC4

Graduate with 8+ years in product / solution management Product Manager / Offering Manager in Cloud, IaaS, HPC, or related high-tech domains. Hands-on understanding of technologies like NVIDIA GPU stacks, containerized HPC (Singularity, Docker), scheduling systems (SLURM, PBS), Lustre / GPFS Familiarity with as-a-Service constructs, subscription models, and TCO discussions. Product lifecycle management. Project and cross-functional stakeholder management Strong articulation, documentation, and influencing ability Able to interact across sales, delivery, product, and finance Suitable candidates may forward their updated profiles in strict confidence to hr33@hectorandstreak.com or call on 9699224920

Role: DevOps Engineer Work Location: Thane, Maharashtra Total Experience: 5 + years Shift: 3 pm 12 am (Mon-Fri) Company Prole AMSYS Group We pride ourselves on 20+ Years of excellence based on the principles of integrity, Honor, and mutual gain. As future decisions are made, we are always keeping in mind the prosperity of the AMSYS Family. Amsys IT Services Pvt Ltd is part of this group, based in Mumbai. Website: http://www.amsysis.com Summary: Were seeking a DevOps engineer with VFX experience [80% DevOps, 20% ML/AI]. Key skills Requirements: 3+ years systems engineering NVidia drivers, system conguration ¢ Log server setup, data space allocation for datasets, checkpoints and logs ¢ 5+ years conguration management engineering ¢ Git, Scons, Rez, pypi, docker, conda, make, cmake ¢ Container development ¢ 3+ years of VFX Pipeline development ¢ Shotgun/Shotgrid, Maya, Houdini ¢ Versioning, build and integration ¢ Asset staging, versioning, deployment and tracking. ¢ Python, C++, Shell Desired: ¢ Knowledgeable about animation studio compute infrastructure, render farms. ¢ Background in machine learning systems, conguration, logging, deployment

Designation - Sr. Consultant Experience in any two of the following programming languages: Python, Java, R, or .Net Proficiency in at least one database technology such as SQL, MongoDB, etc. Hands-on experience with AI stacks, including: PyTorch, TensorFlow, NVIDIA NeMo/NIM, Unsloth Agentic AI frameworks like LangGraph, MS AI Foundry Hugging Face, ChromaDB, FAISS, etc. Experience with MLOps and AI deployment infrastructure Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Knowledge of responsible AI practices, including bias mitigation and ethical AI usage

Role & responsibilities Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product/solution capabilities, and work closely with the engineering team in the development of data solutions Experience in combining multiple modalities and integrate them into a unified system capable of handling multiple types of data, including text, video inputs,and audio. Must have real time experience in large Green and Brown field AI and Computer Vision projects using NVIDIA, Intel Core or similar chipsets Strong foundation in statistics, mathematics, machine learning, and programming and model optimization from large dataset in smart cities or other smart industries Designing and implementing data pipelines for efficient data processing and model deployment. Proficient in developing and implementing machine learning and statistical models Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy Implement analytical models in production by collaborating with software developers and machine-learning engineers

-Design, develop & debug embedded software for ARM, Intel & NVIDIA platforms -Develop & maintain DMA drivers & user-space application software for Linux & Windows -Develop real-time applications using RTOS & manage multi-threaded, pre-emptive systems Required Candidate profile Implement communication protocol (SPI, I2C, UART, TCP/IP / UDP) Create robust, maintainable C/C++ code Support system integration, bring-up activities Experience in MPSoCs & ARM Cortex-A/R/M processor

Designation - Sr. Consultant Experience in any two of the following programming languages: Python, Java, R, or .Net Proficiency in at least one database technology such as SQL, MongoDB, etc. Hands-on experience with AI stacks, including: PyTorch, TensorFlow, NVIDIA NeMo/NIM, Unsloth Agentic AI frameworks like LangGraph, MS AI Foundry Hugging Face, ChromaDB, FAISS, etc. Experience with MLOps and AI deployment infrastructure Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Knowledge of responsible AI practices, including bias mitigation and ethical AI usage

The Senior AI Scientist is a technical role responsible for driving the design, development, and deployment of advanced AI components, models and systems. With 7+ years of experience in artificial intelligence and machine learning, this role is focused on hands-on research, solution prototyping, and enterprise-grade implementation across foundational models, generative AI, and multi-modal applications. The individual is expected to contribute deep technical expertise, execute on complex AI initiatives, and mentor junior scientists. The ideal candidate combines a strong research background with architectural thinking, practical implementation experience, and the ability to collaborate across cross-functional data, business, product and other teams. Responsibilities Develop the organizations AI research agenda, with a focus on AI (NLP/ML models), foundational models, generative AI, Agentic AI solutions and multi-modal systems aligned to business priorities. Develop end-to-end AI components and capabilities, from ideation and prototyping to scalable, enterprise-grade deployment. 3. Translate cutting-edge research into real-world AI components, performance optimization, data generation, and integration with existing data and platform ecosystems. Collaborate cross-functionally across product, business and other teams to drive alignment between AI research strategy and enterprise technology roadmaps. Ensure compliance and optimize performance, covering data governance, industry standards, and model efficiency. Ensure responsible and ethical AI development, incorporating model governance, explainability, fairness, and bias mitigation into the AI lifecycle. The person has to perform testing, validation of the components with reproducible matrix. The person has to perform cross collaboration and work on activities like generation of synthetic data, test suite development, Fine tuning and metrics validation. Good to have - Contribution to Whitepaper, blog authoring / contribution, Github Open source AI projects. Skills Expertise in software languages like Python / Java / .NET, R, PySpark, etc (Atleast 1 language) and SQL Expertise in developing AI and ML based solutions involving LLMs, NLP, Speech, Video, Agentic AI and other Deep Learning based models. Should have worked on Frameworks and libraries like Tensorflow, PyTorch, ScikitLearn, Ollama, Nemo, Transformers, Torch lightning, NIMS library, Unsloth, etc. Should have exposure working on Fine tuning of LLM models using Open source libraries. Ability to pursue new innovative solutions based on the new and latest technological developments and stacks. Ability to validate the solutions based on metrics, components to be part of larger integral system. Experience in Machine learning models like statistical, time series, stochastic, etc. Possess good concepts in various Machine learning algorithms and metrices. Experience in NLP based solutions like extraction, summarization, classification, etc using libraries like RASA, BERT, etc. Experience in developing chatbots, QA solutions, etc. Experience in replicating the solution for different business streams as per the requirement by fine tuning the models. Experience in using AI Cloud services in developing platform / end to end solutions. Good to have exposure to Cloud based deployment of AI solutions Exposure to atleast 1 Cloud services (AWS, Azure, GCP) is expected Should have experience in developing GenAI solutions making use of cache like RAGs (Chroma DB, FAISS, etc) and internal memory. Good to have experience in developing Hash, GraphAI, etc based NLP components like models, RAGs, etc Capable of communicating AI strategy, technical insights, and roadmaps to senior stakeholders for strategic alignment Solid grasp of data privacy, security, and compliance standards in WNS Adaptability and a continuous learning mindset and excellent communication

We are looking for an innovative AI/ML Developer to join our team and contribute to building intelligent systems and data-driven products. The ideal candidate will have experience designing machine learning models, working with large datasets, and deploying algorithms into scalable production environments. You will collaborate with cross-functional teams to transform data into actionable insights and intelligent solutions that drive business impact. Key Responsibilities: Design and develop machine learning and deep learning models. Preprocess and analyze large datasets for feature engineering and model training. Train, validate, and fine-tune models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Deploy models into production using REST APIs, containers, or MLOps tools. Monitor model performance and retrain as needed based on feedback or drift. Collaborate with data engineers and product managers to integrate ML into applications.