**Company: JP02 NVIDIA Japan KK Job Description Summary: NVIDIA is looking for a Data Science focused Solution Architect with expertise in ML, DL, and Data Science platforms. The role involves working with cutting-edge AI computing hardware and software, enabling customer productivity, and developing lasting relationships with technology partners. The Solutions Architect will work with the latest HPC architectures and advanced neural network models to change the way people interact with technology. They will collaborate with key customers and drive relationships with executives and managers to promote accelerated computing. The ideal candidate should have excellent communication skills in Japanese and English, along with a background in Computer Science, Data Science, or related fields. Other requirements include experience in machine learning, deep learning, or data science, as well as the ability to work with multiple teams across organizations. Experience with large-scale distributed DL training, transformer-based architectures, chatbot technologies, DevOps, and HPC systems is a plus. NVIDIA is a leading company in accelerated computing, revolutionizing industries and society. Job Description: NVIDIA’s Worldwide Field Operations (WWFO) team is looking for a Data Science focused Solution Architect with expertise in Machine Learning (ML), Deep Learning (DL) and Data Science platforms. Exposure to inferencing technology (e.g., understanding of model compression techniques, model compilation or model serving) would be an added value. In our Solutions Architecture team, we work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence. We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always thinking about artificial intelligence, someone who can maintain synergy in a fast paced, rapidly evolving field, someone able to coordinate efforts between corporate marketing, industry business development and engineering. You will be working with the latest HPC architectures coupled… with the most advanced neural network models, changing the way people interact with technology. As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to evangelize accelerated computing. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns. What You’ll Be Doing: Develop and demonstrate solutions based on NVIDIA’s state-of-the-art AI and ML software and hardware technologies to customers. Work directly with key customers to understand their technology and provide the best solutions. Perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems. This includes support in optimization of both training and inference pipelines. Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations. Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures. What We Need to See: Excellent verbal, written communication, and technical presentation skills in Japanese. Business level English communication is also a requirement. MS/PhD in Computer Science, Data Science, Electrical/Computer, or equivalent experience Engineering, Physics, Mathematics, other Engineering fields. 3+ years of academic and/or industry experience in fields related to machine learning, deep learning and/or data science. You are excited to work with multiple levels and teams across organizations (Engineering, Product, Sales and Marketing team). You are a self-starter with attitude for growth, passion for continuous learning and sharing findings across the team. Ways to Stand Out from The Crowd: Experience running large scale distributed DL training Background with working with larger transformer-based architectures Expertise with chatbot related technologies such as ASR, TTS, LLMs, or RAG Experience using DevOps technologies such as Docker, Kubernetes, Singularity, etc Understanding of HPC systems: data center design, high speed interconnect InfiniBand, cluster storage and scheduling related design and/or management experience NVIDIA is a Learning Machine NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and the metaverse is transforming the world’s largest industries and profoundly impacting society. Learn more about NVIDIA
Company:JP02 NVIDIA Japan KK
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Level of experience (years):Senior (5+ years of experience)
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
