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Mô tả công việcBuild and training pipelines for Generative AIImplement, optimize with state-of-the-art computer vision modelsCollaborate with teams to integrate computer vision algorithms into larger AI systems and applications.Stay up-to-date with the latest advancements in computer vision research and apply them to enhance our AI projects.Yêu cầu công việcFinal year students or fresh graduates with GPA above 3.2/4 or 8.0/10;Education: Top students from Vietnamese universityEnglish: IELTS 6.0, TOEIC 800, or Cambridge C1 (Nice to have)Experience: Fresh graduates or candidates with less than 2 years of experience.Employment Type: Full-time.Proficiency in programming languages such as Python, C++, or similar, along with experience in deep learning frameworks (e.g., PyTorch).

BẤM NÚT APPLY/ ỨNG TUYỂN ĐỂ XEM THÊM THÔNG TIN CHI TIẾTWhat You’ll Do AI Systems and Hardware-Aware Modeling Explore AI workflows and develop scripts/models that assist in IC calibration, prediction, or optimization.Specialized model building and fine-tuning for circuit exploration, design, validationContribute to prototyping and automation tasks involving Python, PyTorch, or other ML frameworks. System Integration Automation Participate in cross-functional work that brings together hardware, software, and algorithm layers.Assist with system-level test setups, data analysis, and verification tasks. Team Collaboration Technical Growth Join a collaborative team environment that encourages asking questions, sharing ideas, and thinking beyond your current domain.Work alongside experienced engineers and researchers to learn best practices and deepen your technical foundation. Why This Internship Matters This internship will give you: Real project experience in one of the world’s leading chip design environmentsExposure to Marvell’s core technologies, toolchains, and product workflowsThe opportunity to explore both depth and breadth—whether you love transistor-level design or aspire to innovate at the system/AI levelA mentorship path that could evolve into a full-time role or thesis opportunity Your Path Forward Many of our interns go on to become key contributors and technical leaders within Marvell. If you’re dreaming of a career that spans deep analog design, AI-driven innovation, and system-level impact—this is where you start.

Mô tả công việcArchitect end-to-end generative AI solutions including Large Language Models (LLMs), multimodal AI systems, and AI-powered applicationsDesign and implement scalable generative AI systems leveraging state-of-the-art models such as GPT, Claude, Llama, and other foundation modelsBuild production-ready generative AI products including conversational AI, content generation, code generation, and intelligent automation systemsDevelop and optimize LLM fine-tuning, prompt engineering, Retrieval-Augmented Generation (RAG), and model alignment techniquesLead cross-functional collaboration with data scientists, ML engineers, product managers, and business stakeholders to deliver complete AI solutionsEstablish MLOps practices for generative AI including model versioning, A/B testing, monitoring, and continuous deploymentMentor engineers and provide technical leadership in generative AI best practices and emerging technologiesResearch and evaluate new generative AI techniques, tools, and frameworks to maintain competitive advantageEnsure responsible AI practices including safety, fairness, privacy, and ethical considerations in all AI systemsYêu cầu công việc3+ years of relevant professional experience in AI/ML with 2+ years specifically in Generative AIDeep expertise in Large Language Models, transformer architectures, and generative AI techniquesHands-on experience with foundation models (GPT-4, Claude, Llama, Gemini) and fine-tuning approaches (LoRA, QLoRA, PEFT)Production experience with generative AI applications including RAG systems, AI agents, and conversational AIStrong programming skills in Python with proficiency in PyTorch, Transformers, LangChain, and modern AI frameworksExperience with cloud platforms (AWS, GCP, Azure) and AI/ML services for model deployment and scalingLeadership experience in guiding technical teams and driving AI product development

AI Engineer with full-stack capabilities in Computer Vision and NLP, supporting the building, testing, and deployment of machine learning models and algorithms. The role works closely with senior engineers and cross-functional teams (product, marketing, data science) to integrate AI features into user-facing products and internal tools. Responsibilities also include improving AI pipeline performance, monitoring and evaluating deployed AI systems in operation, and assisting in the development of AI-powered internal tools such as assistant bots for content generation, marketing workflows, and other internal processes.Mô tả công việcDevelop and test AI-driven features in collaboration with the senior engineering team, focusing on marketing tools, user engagement, and automation products.Assist in building and improving internal AI tools, such as bots for content generation and workflow automation, to enhance team productivity.Support the deployment and maintenance of machine learning models and ensure their effectiveness in production environments.Continuously monitor AI systems and suggest improvements based on user feedback and system performance.Work in an agile environment, participating in sprint planning, development, and testing cycles.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.Basic understanding of AI/ML concepts and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.Proficiency in programming languages like Python, with a solid understanding of coding practices and principles.Familiarity with data manipulation and analysis tools (e.g., Pandas, NumPy).Familiarity with cloud platforms (AWS, GCP, Azure) is a plus.Strong analytical and problem-solving skills, with a willingness to learn and adapt to new technologies and challenges.Good communication skills and the ability to work collaboratively within a teamExperience with project about Computer vision and NLP

The Senior Lead Storage and Server Test Engineer will play a pivotal role in the design, development, and execution of comprehensive test strategies for our AI data center's storage and server infrastructure. This leadership position requires deep expertise in enterprise storage systems, server architectures, networking, and a strong understanding of the unique performance and reliability demands of AI/ML workloads. The ideal candidate will be a hands-on technical leader, capable of mentoring junior engineers, driving test automation, and collaborating across engineering teams to deliver robust and high-performing solutions.Required Qualifications• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field.• 3+ years of experience in hardware and/or software testing, with at least 5 years focused on enterprise-level storage and server systems.• Proven experience in a lead or senior technical role, mentoring and guiding other engineers.• Deep expertise in various storage technologies including NVMe, SAS/SATA SSDs/HDDs, RAID, distributed file systems (e.g., Ceph, Lustre, GPFS), SAN, and NAS.• Strong understanding of server architectures (x86, ARM, GPU servers), CPU/memory subsystems, PCIe, and power management.• Strong understanding of server architectures (x86, ARM, GPU servers), CPU/memory subsystems, PCIe, power management, and Baseband Management Controllers (BMC) functionality.• Proficiency in scripting languages (e.g., Python, Bash) for test automation and data analysis.• Experience with Linux operating systems (e.g., Ubuntu, CentOS, RHEL) and command-line tools.• Familiarity with networking concepts (Ethernet, TCP/IP, InfiniBand) and network testing methodologies.• Experience with test methodologies such as performance testing, reliability testing, stress testing, and fault injection.• Excellent problem-solving, analytical, and debugging skills.• Strong communication and interpersonal skills, with the ability to collaborate effectively across diverse teams.Preferred Qualifications• Familiarity with OCP (Open Compute Project)• Experience with cloud environments (AWS, Azure, GCP) and virtualization technologies.• Knowledge of containerization technologies (Docker, Kubernetes).• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) and their infrastructure requirements.• Experience with performance profiling tools (e.g., fio, Iometer, Perf, VTune).• Contributions to open-source projects related to storage, servers, or testing.• Certifications in relevant technologies (e.g., NetApp, Dell EMC, HPE, NVIDIA).

MoMo is the market leader in mobile payments in Vietnam, striving to make all transactions fast, easy, and joyful. You will join our Big Data AI team, where we position AI/Machine Learning as the core component of almost every product feature.Specifically, you will operate as a key technical leader in the Moni team—the squad behind MoMo's flagship AI Assistant. Moni currently serves hundreds of thousands of Monthly Active Users, scaling from a chatbot into a fully autonomous AI Agent. As a Senior / Technical Lead, you will drive the architectural decisions and engineering standards that power the next generation of our Agentic AI.Mô tả công việcTechnical Leadership Architecture:Define the technical vision and architecture for autonomous AI Agents.Make critical decisions on tech stacks, model selection, and system design to ensure scalability and reliability.Architect Build AI Agents: Lead the end-to-end development of complex Agentic workflows (Tool Calling, Planning, Reasoning) that integrate deep into the MoMo ecosystem.Multi-Agent Orchestration: Design and implement orchestration layers where multiple specialized agents collaborate to solve intricate user financial tasks.Advanced RAG Strategy: Engineer robust RAG pipelines (Hybrid Search, GraphRAG, Re-ranking) to handle vast knowledge bases with high precision.System Evaluation Quality Assurance: Establish "Gold Standard" evaluation frameworks for Agentic AI (reasoning capabilities, hallucination rates, safety metrics) and drive the optimization loop.Mentorship Best Practices: Mentor senior/junior engineers, conduct code reviews, and set high standards for code quality, MLOps practices, and GenAI engineering across the team.Production Excellence: Partner with DevOps/MLOps to ensure high availability and low latency for AI services serving massive concurrent traffic.Yêu cầu công việcExperience: 5+ years of professional experience in AI/ML/Software Engineering, with a strong track record in leading technical initiatives.Agentic AI Mastery: Deep hands-on experience in building AI Agents and Multi-Agent systems. Proficient in Agentic Design Patterns like Tool Calling, Planning and Reasoning, and frameworks such as LangChain, LangGraph, or Agents SDK.Advanced RAG Search: Expert knowledge of retrieval strategies, vector databases, and semantic search optimization.LLM Model Strategy: Strong capability in selecting and benchmarking Foundation Models (Open vs. Closed source) and applying fine-tuning/alignment (RLHF, DPO) strategies.System Evaluation: Experience implementing rigorous evaluation pipelines for Agentic AI (using Ragas, Langfuse, or custom metrics).Engineering Excellence: Proficient in Python, PyTorch, and modern Data/AI stacks. Experience in designing high-load distributed systems is a plus.Leadership Mindset: Ability to navigate ambiguity, drive technical consensus, and balance engineering perfection with product delivery speed.

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience with software development in one or more programming languages. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. Preferred qualifications: Experience working with data science tools such as Jupyter notebooks, Open Telemetry, JMX and other monitoring solutions. Experience with Database optimizations - query and executor optimizations and Data lakes like Apache Iceberg, Apache Hudi, Delta lake, etc. Experience with OSS projects like Spark, Hive, Trino and in benchmarking and building custom benchmarks. Experience in developing Cloud or SaaS products. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Join the Google Cloud Dataproc team and build the next generation of data processing, combining the best of open source with Google's innovation. We are not just managing Apache Spark and Hadoop clusters; we are fundamentally accelerating big data. For engineers passionate about the future of data, you will be building an AI/ML-ready platform, leveraging native GPU support and specialized run times pre-packaged with PyTorch, TensorFlow, and RAPIDS, integrated with Vertex AI for ML Operations. This is where you architect the unified, open lake house of tomorrow, seamlessly connecting with formats like Apache Iceberg, Delta, Hudi and providing enterprise-grade security and scale that empowers the world's most demanding data scientists and engineers.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Lead the development of next-generation features, positioning Cloud Dataproc as the preferred platform for Spark, Flink, Trino, and emerging cloud technologies. Define the road map for enhancing open-source technologies like Spark, Hive, Trino, Iceberg, Hudi, and Delta into Dataproc. Drive the design and implementation of Data Lakes and Lake Houses, including Apache Iceberg and Hudi along with ehnancing the performance and efficiency of open-source technologies within the platform. Develop and implement software solutions leveraging Google technologies for accelerated cluster setup, streamlined operations, and monitoring. Establish benchmarks to identify and resolve performance bottlenecks, ensuring Spark job certification. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Computer Science, Data Science, a related field, or equivalent practical experience. 6 years of experience as a technical sales engineer in AI/ML, or in a software engineering role. Experience in Python and Machine learning frameworks (e.g., TensorFlow, PyTorch). Experience delivering technical presentations and leading business value sessions. Experience in Generative AI as a developer. Ability to communicate in English and Korean fluently as this is a customer-facing role that requires interactions with the local stakeholders. Preferred qualifications: Experience in designing and deploying multi-agent architectures with Agent Development Kit (ADK), and integrating next-gen Generative AI models (e.g., Gemini, Imagen, Veo) to build dynamic applications. Experience with core search concepts like indexing and query rewriting. Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches. Understanding of implementation and optimized Retrieval-Augmented Generation (RAG) models using both first-party and open-source models. Ability to travel up to 20% of the time. About the jobIn this role, you will support Google Cloud Sales and Engineering teams to incubate, pilot, and deploy Google Cloud’s Artificial Intelligence/Machine Learning (AI/ML) and Generative AI technology with AI native customers, large enterprises, and early-stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators Tensor Processing Unit/Graphics Processing Unit (TPU/GPU). You will identify, assess, and develop GenAI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and help to analyze cost to performance. You will work with internal Cloud AI teams to remove roadblocks and shape the future of offerings.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Advise customers by understanding their business processes and objectives. Architect AI-driven solutions spanning Data, AI, and Infrastructure, and work with peers to include the full cloud stack in the overall architecture. Work with customers on application prototypes, demonstrating Generative AI features, prompting and tuning models, optimizing model performance, profiling, benchmarking, and troubleshooting to find solutions to issues in Generative AI applications. Build repeatable technical assets such as scripts, templates, reference architectures, to enable other customers and internal teams. Coordinate regional field enablement with leadership and work with product and partner organizations on external enablement activities. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and Artificial Intelligence/Machine Learning (AI/ML) by advocating for enterprise customer requirements. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 6 years of experience with writing code in one or more general purpose programming languages (e.g., C++, Java, Python, Go, etc). Experience with Linux/Unix systems with debugging issues across the hardware/software boundary on enterprise-grade server infrastructure. Experience in troubleshooting for customer needs, and triaging technical issues across the stack (e.g., hardware faults, networking, virtualization, kernel drivers, firmware, performance). Preferred qualifications: Experience in working with distributed systems with the knowledge of common solutions, design patterns, or best practices. Experience in working with Artificial Intelligence/Machine Learning (AI/ML) computing hardware, including Graphics Processing Unit (GPUs) or other accelerators. Experience with containerization and orchestration technologies like Kubernetes or Slurm. Experience with ML frameworks (e.g., TensorFlow, Pytorch), with the knowledge of the AI/ML training and inference lifecycle. Excellent troubleshooting and communication skills with attention to details. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate. In this role, you will own customer issues and provide specialized support to other teams. You will be a part of a global team that provides support to ensure customers can deploy their Artificial Intelligence (AI) and Machine Learning (ML) workloads on AI Infrastructure products. You will troubleshoot technical problems with hardware and software debugging, networking, Linux system administration, coding/scripting, and updating documentation. You will help the customer’s success in the AI/ML space by making improvements to the product, internal tools, processes, and documentation. You will help drive business growth by recognizing and advocating for the customers’ tests related to AI deployments.Responsibilities Manage customer’s problems through diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure. Develop an understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer reported issues, and building tools for diagnosis. Act as a consultant and subject matter expert for internal stakeholders in Engineering, Business, and customer organizations to resolve deployment and operational obstacles in AI infrastructure environments. Work with multiple Product and Engineering teams to find ways to improve the product, and interact with our Site Reliability Engineering (SRE) teams to drive production. Be available for non-standard work hours or shifts which may include weekends as needed. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 8 years of experience in Python or other programming languages in machine learning (e.g., Java, C++, Go). Experience with python and Machine Learning frameworks (e.g., TensorFlow, PyTorch). Experience with Generative AI as a developer. Experience delivering technical presentations. Ability to communicate in English and Japanese fluently to interact with internal and external stakeholders. Preferred qualifications: Google Cloud Platform (GCP) Professional and certified Machine Learning Engineer. Experience architecting Machine Learning Operations (e.g., MLOps) systems in enterprise environments and in building enterprise-grade machine learning systems. Experience working with batch and online model serving with an understanding of model management and monitoring. Knowledge of vertex AI model deployment, and vertex pipelines, kubeflow, or MLFlow for automation and experimentation. Knowledge of GCP services and how to use them for analytics and data engineering, including BigQuery and Vertex AI. Excellent infrastructure building and maintenance skills on the GCP for data engineering pipelines. About the jobAs an AI/ML Field Solutions Architect, you will support Google Cloud Sales teams and engineering to deploy Google Cloud’s Artificial Intelligence/Machine Learning (AI/ML) and Generative Artificial Intelligence (Gen AI) technology at AI natives and innovators, enterprises, and AI startups. You will help customers innovate with the solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators Tensor Processing Unit/Graphics Processing Unit (TPU/GPU).In this role, you will identify, assess, and develop GenAI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud road-maps by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. Along the way, you will work with internal Cloud AI teams to remove roadblocks and shape the future of our offerings. You will navigate ambiguity, troubleshoot and find solutions, and learn in the technology space.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Lead the Japan-based Field Solutions Architect (FSA) team as their team lead. Serve as a consultant for clients by grasping their operational needs and goals. Design AI-focused architectures that encompass data, infrastructure, and AI, collaborating with teammates to integrate the complete cloud stack. Emphasize the advantages of Google Cloud through proof-of-concept projects, feature displays, model tuning, and performance optimization. Resolve issues related to model training and serving. Develop reusable technical resources such as reference architectures and templates to assist internal teams and other clients. Influence the evolution of Google Cloud products by advocating enterprise needs at the crossroads of AI/ML and infrastructure. Oversee regional field readiness in partnership with leadership and collaborate with product and partner teams on external training initiatives. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.