דרושים Ai Research Intern Tao Multi-modal Model Development - ב-אנבידיה ב-Vietnam, Thái Nguyên

What you'll be doing:

• Feature Development: Designing, developing, and implementing new dashboard features and user interface improvements using React and TypeScript.

• Responsive Design: Translating wireframes and prototypes from designers into high-quality, pixel-perfect, and responsive web components and layouts.

• Code Quality & Maintenance: Identifying, troubleshooting, and resolving bug fixes, optimizing component performance, and maintaining code health across the application.

• API Integration: Integrating with and consuming modern web APIs to fetch, display, and manipulate dynamic data within the user interface.

• Prototyping: Rapidly building and iterating on functional prototypes to test new ideas and gather user feedback.

• Collaboration: Working closely with product managers, UX designers, and senior engineers to understand requirements, participate in code reviews, and deliver high-impact solutions.

What we need to see:

• Currently enrolled in a Bachelor's or Master's program in Computer Science, Software Engineering, or a related technical field.

• Strong foundational knowledge of web development principles (HTML, CSS, JavaScript).

• Proficiency in TypeScript and hands-on experience with a modern frontend framework (React is strongly preferred).

• Understanding of (or strong interest in) modern web APIs (e.g., RESTful services) and asynchronous programming.

• A curious and proactive mindset. We are seeking individuals who demonstrate initiative, write clean code, and assume responsibility for their project deliverables.

• Excellent problem-solving and communication skills.

Ways to stand out from the crowd:

• A demonstrated passion for building intuitive, fast, and user-friendly web applications.

• Familiarity with the modern web development ecosystem (e.g., Git, npm/yarn, testing frameworks).

• Experience with responsive design principles and CSS-in-JS or pre-processors (e.g., Sass).

• Knowledge of backend development (e.g., Node.js, Express) or database systems (SQL or NoSQL).

• Previous project or internship experience involving web development.

What You’ll Be Doing:

• Lead and grow a high-impact engineering team focused on AI-enabled signal processing for the Radio Access Network (RAN).

• Guide the development of deep learning models for tasks such as channel estimation, beamforming, link adaptation, and CSI compression.

• Collaborate with global teams across architecture, research, and systems to drive proof-of-concepts and production-quality AI-RAN components.

• Oversee integration of AI models into full-stack simulations and/or testbeds using frameworks such as PyTorch, TensorFlow, and NVIDIA Sionna.

• Align project priorities with hardware-software co-design constraints and deployment scenarios on NVIDIA platforms.

• Mentor team members, ensure technical excellence, and contribute to strategic direction.

What We Need to See:

• MS or PhD in Electrical Engineering, Computer Engineering, or related field.

• 10+ overall years of experience in wireless communications, signal processing, or AI/ML, with at least 3+ years of technical leadership experience.

• Deep understanding of wireless PHY/MAC systems, including MIMO, OFDM, and adaptive filtering.

• Proven experience developing or deploying neural network architectures (e.g., CNNs, Transformers) in real-world AI or signal processing applications.

• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.

• Strong collaboration and communication skills across multi-disciplinary teams and geographies.

Ways to Stand Out from the Crowd:

• Experience with AI for 5G/6G systems, AI-for-RAN architecture, or telecom-grade deployments.

• Knowledge of channel estimation by AI, model compression, real-time inference, or GPU optimization

• Familiarity with RIS, massive MIMO, or THz communication challenges.

• Track record of research, publications, or open-source contributions in AI-for-wireless.

What You’ll Be Doing:

• Design and prototype deep learning models for wireless signal processing tasks such as channel estimation, beam alignment, link adaptation, and scheduling.

• Work with simulation tools and real-world datasets to build models that generalize across diverse wireless scenarios.

• Implement, train, and validate neural networks (e.g., CNNs, Transformers, GNNs) using PyTorch or TensorFlow.

• Collaborate with researchers and system engineers to integrate models into full-stack RAN.

• Optimize model performance for real-time inference and hardware acceleration.

• Contribute to model evaluation, benchmarking, and deployment readiness on GPU platforms.

What We Need to See:

• MS or PhD in Electrical Engineering, Computer Engineering, or a related field (or equivalent experience).

• 12+ years of experience in wireless communications, signal processing, or AI/ML.

• Deep understanding of communication systems (e.g., MIMO, OFDM, fading channels) and DSP fundamentals.

• Strong experience in training and deploying deep learning models for time-series or signal-based tasks.

• Proficiency in Python and experience with DL frameworks like PyTorch or TensorFlow.

• Familiarity with tools such as MATLAB, GNU Radio, or NVIDIA Sionna for wireless simulation.

Ways to Stand Out from the Crowd:

• Experience with AI for 5G/6G systems, AI-for-RAN architecture, or telecom-grade deployments.

• Knowledge of channel estimation by AI, model compression, real-time inference, or GPU optimization

• Exposure to CUDA, Triton, or real-time inference pipelines.

• Contributions to research publications or open-source wireless/AI projects.

What you'll be doing:

• Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks.

• Contribute to the design and implementation of vision-language models (VLMs) and universal segmentation systems.

• Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability.

• Collaborate with cross-functional teams to integrate your research into production-level pipelines and NVIDIA SDKs.

• Participate in research discussions, code reviews, and technical documentation to share insights and improve methodologies.

What we need to see:

• Currently pursuing a degree in Computer Science, Computer Engineering, or a related field.

• Proven experience with machine learning, deep learning, or computer vision model development.

• Strong Python programming skills and proficiency with PyTorch or similar frameworks.

• Solid understanding of neural network architectures, transformers, and multi-modal learning techniques.

• Excellent problem-solving abilities, attention to detail, and a collaborative mindset.

• Familiarity with vision-language models, image segmentation, or large-scale pretraining is a strong plus.

What you'll be doing:

• You will develop generative models for protein backbone/structure generation, prediction, and molecular docking using NVIDIA technology.

• Collaborate with AI experts to implement and refine algorithms.

• Conduct research and experimentation to enhance model performance.

• Work closely with cross-functional teams to integrate your models into existing platforms.

• Participate in regular team meetings to discuss progress and determine next research steps.

What we need to see:

• Currently pursuing a degree in Computer Science, Computer Engineering, or a related field.

• Proven experience with machine learning, and generative AI model development.

• Strong programming skills in Python, its libraries, and deep learning frameworks like PyTorch.

• Outstanding problem-solving abilities and strong attention to detail.

• Ability to work collaboratively in a diverse and inclusive environment.

• Familiarity with protein engineering, biotechnology, and molecular biology is a strong plus.

What You’ll Be Doing:

• Build, lead and scale world-class engineering teams in Vietnam, collaborating with global counterparts across system software, data science, and AI platforms.

• Drive the design, architecture, and delivery of high-performance system software platforms that power NVIDIA’s AI products and services.

• Partner with global teams across Machine Learning, Inference Services, and Hardware/Software integration to ensure performance, reliability, and scalability.

• Oversee the development and optimization of AI delivery platforms in Vietnam, including NIMs, Blueprints, and other flagship NVIDIA services.

• Engage with open-source and enterprise data and workflow ecosystems (e.g., Temporal, Gitlab DevOps Platform, RAPIDS, NeMo Curator, Morpheus) to advance accelerated AI factory, data science and data engineering workloads.

• Champion continuous integration, continuous delivery, and engineering best practices across multi-site R&D Centers.

• Collaborate with product management and cross-functional stakeholders to ensure enterprise readiness and customer impact.

• Develop and deploy standard processes for large-scale, distributed system testing, encompassing stress, scale, failover, and resiliency testing.

• Ensure security and compliance testing aligns with industry standards for cloud and data center products.

• Mentor and develop talent within the organization, fostering a culture of quality and continuous improvement.

What We Need to See:

• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or related field.

• 15+ overall years of software engineering experience with 6+ years in senior leadership roles.

• Proven record of managing large, high-performing software teams and delivering complex AI/ML or data-driven products.

• Expertise in cloud, data, and accelerated computing technologies (e.g., Spark, Kubernetes, Dask, Python ecosystem, CUDA).

• Experience collaborating with open-source communities and enterprise partners.

• Strong leadership, communication, and cross-functional coordination skills.

• Strategic mindset with hands-on technical depth in AI, system software, or large-scale data platforms.

Ways to Stand Out from the Crowd:

• Experience building and scaling AI/ML Inferencing platforms from concept to production.

• Background in GPU programming, CUDA optimization, or system performance engineering.

• Deep understanding of microservices, distributed systems, and high-performance data architectures.

• Contributions to open-source projects or developer ecosystems.

• Knowledge of deep learning, RAG, embeddings, or modern text search frameworks.