6 Nvidia Jetson Jobs

Job Description Role Summary We are seeking a Generative AI/ML Engineer to design, build, and deploy intelligent AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and edge computing. You will work hands-on with cloud-native AI services, LLMOps pipelines, and enterprise-grade deployment patterns to solve business problems. Key Responsibilities Design, develop, and fine-tune LLM-powered applications for enterprise use cases. Experience in evaluating LLM applications and developing observability frameworks Implement RAG pipelines using vector databases, embeddings, and optimized retrieval strategies. Build agentic AI workflows with multi-step reasoning, tool calling, and integration with APIs. Integrate GenAI solutions into multi-cloud or hybrid cloud environments (AWS, Azure, GCP). Develop and optimize edge AI deployments for low-latency use cases. Create data strategy, ingestion, transformation, enrichment, validations, quality checks via pipelines for AI ingestion, preprocessing, and governance. Implement AI safety, bias mitigation, and compliance measures. Work closely with LLMOps teams to enable continuous integration & deployment of AI models. Write well-documented, production-ready code in Python, Node.js, Rust . Benchmark and evaluate model performance , latency, and cost-efficiency. Required Skills Proficient in cloud AI services (e.g. AWS Bedrock/SageMaker, Azure AI Foundry, Google Vertex AI, Anthropic, OpenAI APIs). Strong proficiency with Python and LLM frameworks (e.g. PromptFlow, LangGraph, LlamaIndex, HuggingFace, PyTorch, TensorFlow). Hands-on experience with vector DBs (e.g. Pinecone, Weaviate, Milvus, FAISS, Azure Cognitive Search). Experience building RAG-based and agentic AI solutions. Familiarity with Edge AI frameworks (e.g. NVIDIA Jetson, AWS IoT Greengrass, Azure Percept). Multi-modal AI (text, image, speech, video) experience. Strong grasp of APIs, microservices, and event-driven architectures . Knowledge of AI governance (data privacy, model explainability, security). Experience in containerized deployments (Docker, Kubernetes, serverless AI functions). Preferred Skills Generative agents with memory and planning capabilities . Real-time AI streaming with WebSockets or Kafka. Prior contributions to open-source GenAI projects . Experience in build, test and deploy various ML models Experience in building MCP, A2A protocol Show more Show less

As an AI ML Engineer with 2 to 5+ years of experience, you will be responsible for understanding complex problem statements, handling and triaging data, and selecting/improving neural network models using deep learning frameworks to address business challenges. Your expertise in Python coding is mandatory, and proficiency in C/C++ or Java is an added advantage. You will leverage your experience to develop AI/ML/DL models through transfer learning or from scratch. A good understanding of leading deep learning frameworks such as TensorFlow, PyTorch, ONNX, and Keras is essential. Additionally, you will have working experience with computer vision models like Yolo, Mobilenet, and Resnet. Your role will also involve working with AI/ML/DL on Edge platforms like Nvidia Jetson family, Qualcomm, Intel, and Rpi. You should be well-versed in the complete DL/AI/ML lifecycle, from data collection to model building, experimental framework, and data analytics. Experience in developing and optimizing models in various computing domains such as Video, Statistics, and Audio is crucial. You should have a demonstrated track record of completing data science projects with minimal supervision and possess a conceptual understanding of different modeling techniques and their advantages and disadvantages. An added advantage would be a proven record of migrating AI/ML/DL models/algorithms to low-level platforms and familiarity with optimizing code for minimal CPU and memory usage. This is a full-time position located at IN-GJ-Ahmedabad, India-Ognaj (eInfochips) in the Engineering Services category.,

It is exciting to be a part of a company where individuals truly BELIEVE in the mission at hand! The commitment is to infuse passion and customer-centricity into every aspect of the business. Fractal, a key player in the Artificial Intelligence domain, is dedicated to empowering human decisions within enterprises by merging AI, engineering, and design to support Fortune 500 companies globally. With over 3,000 employees spread across 16 international locations, including the United States, UK, Ukraine, India, Singapore, and Australia, Fractal has consistently been recognized for its excellence. Notable achievements include being rated as one of India's best companies to work for by The Great Place to Work Institute, acknowledged as a leader in Customer Analytics Service Providers Wave 2021, Computer Vision Consultancies Wave 2020, and Specialized Insights Service Providers Wave 2020 by Forrester Research, and identified as an "Honorable Vendor" in Gartner's 2021 Magic Quadrant for data & analytics. The team at Fractal is currently in search of an innovative and motivated Solutions Architect to join the expanding Edge & IoT team. In this role, you will collaborate closely with clients and internal engineering teams to conceptualize and implement efficient edge computing and IoT solutions. Leveraging our expertise in AI/ML and strategic partnerships with industry leaders like Microsoft, Intel, and Nvidia, you will showcase a high level of technical proficiency, comprehend client needs effectively, and deliver cutting-edge, top-quality solutions. To excel in this position, having a robust technical foundation in AI/ML and Edge Computing is essential, along with exceptional communication skills, the ability to think critically and creatively, and the capacity to adapt swiftly to new challenges. A successful Edge AI Solutions Architect will possess a deep understanding of both technological and business requirements, translating complex concepts into user-friendly solutions that drive client success and satisfaction. If you are prepared to contribute to a dynamic and progressive organization, we invite you to apply for this role. Key Responsibilities: - Collaborate with clients to collect requirements, grasp business objectives, and translate them into technical specifications for the engineering team. - Design innovative Edge & IoT solutions, integrating AI/ML components and utilizing cloud platforms like Azure, AWS, and GCP. - Contribute to and lead the development of Edge & IoT accelerators and PoVs. - Design, select, and deploy various IoT hardware components, considering factors such as power consumption, connectivity, interoperability, and environmental constraints. - Develop and present solution architecture and design documents, including diagrams, data flowcharts, and system requirements. - Work with engineering teams to ensure proper implementation of designed solutions and offer technical guidance throughout the project lifecycle. - Act as a mentor for team members, providing guidance, sharing knowledge, and fostering a collaborative and supportive learning environment within the Edge & IoT team. - Serve as a subject matter expert in Edge & IoT technologies, staying updated on industry trends, emerging technologies, and best practices. - Support the account team in the pre-sales process by providing technical assistance and insights into solution proposals. - Contribute to thought leadership initiatives and actively participate in internal trainings and knowledge-sharing sessions. Technical Skills Required: - Proficiency in IoT protocols like MQTT, CoAP, and AMQP. - Knowledge of edge computing technologies and platforms such as Azure IoT Edge, AWS Greengrass, or Google Edge IoT Core. - Understanding of AI/ML algorithms and frameworks, with experience in implementing them in Edge & IoT scenarios. - Experience with IoT devices, sensors, and connectivity solutions, along with cloud-based IoT platforms like Azure IoT Hub, AWS IoT Core, and Google Cloud IoT. - Proficiency in programming languages such as Python, C#, C/C++, or JavaScript. - Familiarity with containerization technologies (e.g., Docker) and orchestration platforms (e.g., Kubernetes, K3S). - Strong understanding of networking concepts, protocols, and technologies, as well as experience in designing secure, reliable, and scalable network architectures for IoT and edge computing solutions. - Knowledge of various hardware platforms such as Raspberry Pi, Arduino, NVIDIA Jetson, Intel NUC, and the ability to choose the appropriate platform based on specific requirements and constraints. - Expertise in packaging and deploying AI and ML models on edge devices using common AI frameworks like TensorFlow, PyTorch, or ONNX Runtime, and optimizing these models for efficient execution at the edge. - Design experience in IoT and edge computing solutions focusing on physical security, device management, thermal management, and enclosure design. - Ability to assess compatibility, interoperability, and performance of hardware components and integrate them into a structured solution architecture. - Understanding of industry standards, regulations, and best practices related to IoT hardware selection, deployment, and security. Qualifications: - Bachelor's or master's degree in computer science, Engineering, or related field. - Minimum 10-12 years of experience in designing and implementing IoT and edge computing solutions, with at least 4-5 years specializing in Edge AI and/or AI/ML integration. - Strong communication and presentation skills. - Excellent problem-solving abilities and attention to detail. - Capacity to work independently or as part of a team. If you thrive in a dynamic environment and enjoy collaborating with enthusiastic, high-achieving colleagues, you will find fulfillment in your career at Fractal!,

The role requires you to create intuitive user interfaces and manage edge deployments for AI applications, ensuring seamless functionality across various naval environments and devices. Your responsibilities will include designing and building responsive and secure interfaces, packaging and deploying applications on different platforms, and ensuring usability in network-constrained or offline environments. You will be developing UI interfaces for dashboards, alerts, geo-spatial visualization, and analytics, integrating with AI outputs from the backend, and building Electron-based desktop apps and Flutter-based mobile clients for offline use. Additionally, you will need to ensure local caching, secure data handling, session management, and implement UI analytics for user interaction tracking. Working closely with end users for field testing and feedback, you will be responsible for compliance with design constraints such as minimal memory footprint, low power consumption, and rapid boot. The ideal candidate should have a B.Tech/M.Tech in Computer Science or related field with a strong foundation in user interface design and human-computer interaction. Desired certifications include Google UX Design Professional Certificate, Adobe Certified Expert in UX Design, and Mobile app development certifications. Core skills and tools required for this role include proficiency in JavaScript, TypeScript, HTML5, CSS3, React, Vue.js, Angular, React Native, Flutter, D3.js, Leaflet, WebSocket, Docker, and Electron. Experience with modern frontend frameworks, mobile app development, responsive design, version control, and collaborative development is essential. Strong communication skills, the ability to mentor junior developers, and experience with micro-frontend architectures are also desired qualifications. If you are interested in this position, please apply by sending your resume to nk@bluparrot.in and JK@Bluparrot.in.,

Capgemini Invent is the digital innovation, consulting, and transformation brand of the Capgemini Group. As an Edge AI Data Scientist, you will be responsible for designing, developing, and validating machine learning models, particularly in the domain of computer vision, for deployment on edge devices. This role entails working with data from cameras, sensors, and embedded platforms to enable real-time intelligence for applications such as object detection, activity recognition, and visual anomaly detection. Collaboration with embedded systems and AI engineers is essential to ensure that models are lightweight, efficient, and hardware-compatible. To be successful in this role, you should have a Bachelor's or Master's degree in Data Science, Computer Science, or a related field, along with at least 3 years of experience in data science or machine learning with a strong focus on computer vision. Experience in developing models for edge deployment and real-time inference, familiarity with video/image datasets, and deep learning model training are also required. Proficiency in Python and libraries such as OpenCV, PyTorch, TensorFlow, and FastAI is essential. Additionally, you should have experience with model optimization techniques (quantization, pruning, etc.) for edge devices, deployment tools like TensorFlow Lite, ONNX, or OpenVINO, and a strong understanding of computer vision techniques (e.g., object detection, segmentation, tracking). Familiarity with edge hardware platforms, processing data from camera feeds or embedded image sensors, strong problem-solving skills, and the ability to work collaboratively with cross-functional teams are all important skills for this role. Your responsibilities will include developing and training computer vision models tailored for constrained edge environments, analyzing camera and sensor data to extract insights and build vision-based ML pipelines, optimizing model architecture and performance for real-time inference on edge hardware, validating and benchmarking model performance on various embedded platforms, collaborating with embedded engineers to integrate models into real-world hardware setups, and staying up-to-date with state-of-the-art computer vision and Edge AI advancements. At Capgemini, we value flexible work arrangements to provide support for maintaining a healthy work-life balance. Our focus is on your career growth, offering a variety of career growth programs and diverse professions to support you in exploring a world of opportunities. You will have the opportunity to equip yourself with valuable certifications in the latest technologies such as Generative AI. Capgemini is a global business and technology transformation partner, helping organizations accelerate their transition to a digital and sustainable world while creating tangible impact for enterprises and society. With a team of over 340,000 members in more than 50 countries, Capgemini leverages its 55-year heritage to deliver end-to-end services and solutions utilizing strengths from strategy and design to engineering, with market-leading capabilities in AI, cloud, and data, combined with deep industry expertise and a partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.,

Role & responsibilities : Job Title / Designation: Solution Architect/Project Manager/Associate Director based on experience & expertise Business Unit : Embedded Engineering Services (EES) Industry Experience Range : 8+ years Job Location : Preferably Pune / Ahmedabad / Bangalore Shift : General Shift (Mon-Fri) Job Function, Roles & Responsibilities: Lead strategic initiatives and own the practice for Edge AI/ML, data pipelines, and intelligent embedded systems Define and build the competency roadmap for machine learning, deep learning, model deployment, and real-time inferencing on edge platforms Oversee data creation including data collection, dataset curation, annotation, cleaning, augmentation, and synthetic data generation Champion use cases involving sensor fusion, combining data from multiple sources (vision, IMU, radar, audio, etc.) to create robust, efficient, and context-aware edge intelligence solutions Drive edge analytics and on-device learning across verticals such as Industrial Automation, Medical Devices, Automotive, and Smart Consumer Electronics Collaborate with global customers to gather requirements, architect solutions, track project delivery, and ensure alignment with business objectives Support business development with presales solutioning, proposal writing, and effort estimation Drive internal capability building through mentoring, training, and competency development Preferred candidate profile: ________________________________________ Experience: 8+ years in embedded systems, AI/ML, and data engineering, with a strong focus on edge intelligence and real-time systems. At least 3 years in a technical leadership or strategic role. Prior experience in a product engineering services environment preferred. ________________________________________ Area of Expertise: Proven expertise in deploying ML/DL models on edge devices (NVIDIA Jetson, NXP i.MX, Qualcomm QCS, TI Sitara, etc.) Strong knowledge of data workflows: dataset generation, manual/automated annotation, data cleaning, augmentation, and synthetic data creation Deep understanding of sensor fusion techniques combining inputs from vision, audio, IMU, radar, LIDAR, and other sources to improve model accuracy and efficiency Experience in model optimization using TensorRT, ONNX, OpenVINO, TFLite, and TVM Hands-on with TensorFlow, PyTorch, scikit-learn, and signal/image processing techniques Proficient in designing for real-time inference on resource-constrained platforms Exposure to AI accelerators, NPUs, DSPs, and hybrid SoC environments; must have exposure to NVIDIA SoC & Tools Presales, account engagement, and solutioning experience with North American or European clients ________________________________________ Nice to Have: Cloud-edge integration using AWS Greengrass, Azure IoT Edge, GCP Edge TPU Understanding of AI regulatory/safety standards (ISO, IEC, FDA compliance for AI/ML in regulated industries) ________________________________________ Educational Criteria: BE/ME/B.Tech/M.Tech Electronics, Computer Science, AI/ML, Embedded Systems, or Data Science ________________________________________ Travel: Flexibility to travel globally with sales or delivery teams for customer meetings, workshops, and project deployments as needed. Interested and qualified candidate can directly reach Mr. Anup Sharma at 99099-75421 or anup.s@acldigital.com. (staffing partner can communicate over the email)