Researcher - AI

Key Skills

AI technology, Apache Hadoop, Deep Learning, Machine learning techniques, Natural language generation- NLG, Natural Language Processing (NLP), Python Programming, Scala Programming, SPARK Programming, SQL, Storm

Job Description

Our team has an immediate permanent opening for an AI Researcher.

Responsibilities:

• Design new generation of AIGC powered applications, through building large foundation models’ (such as ChatGPT/GPT4) capabilities into real world valuable applications to help reinvent productivity.
• Analyze the gaps in existing applications which blocks people from doing the most important parts of their work, and creatively envision the radical changes that recent AIGC techniques can bring to significantly increase the productivity when using traditional tools which require steep learning curve or expert-level professional skills.
• Research and prototyping of modern AIGC methods, to utilize good intuition and practical experience and keen interest to transform foundation model’s selected capabilities into the target applications.
• Report and present research findings and developments, including status and results, clearly and efficiently, both internally and externally, verbally and in writing. Communicate results internally and at conferences.
• Team collaboration in the development and operations of internal software infrastructure for AIGC related algorithms and tools.
• Collaborate on the provisioning and management of on-premises and cloud infrastructures.

Job requirements

What you'll bring to the team:

• Major in Computer science or related field. Master and above is preferred.
• Real passion and experience in AI generative area and keen interest of transforming research oriented foundation models into valuable and accessible real-life applications.
• Practical experience in research of AI models, e.g. transformers, diffusion models, VAE/GAN. Familiarity with recent AIGC models, e.g. large language models (chatgpt, GPT4), multimodal foundation models [Vision and text and code and beyond] (CLIP, DALL-E2, Stable Diffusion, Codex), and deep knowledge of the capabilities and limitations of these models.
• Familiarity with the following: deep learning frameworks, NLP-context understanding and topic tracking; NLG-summarization, prompt engineering, instruction tuning, RLHF, chatbot building, Vision Question and Answering/Captioning, text-to-image generation.
• Awareness of considerations in retraining/finetuning large foundation models, and corresponding cost-effective use.
• Good understanding of machine learning and AI, especially recent foundation models, in-context learning and zero-shot and few-shot learning.
• Good at Data analytics and relevant programming languages, e.g., Python, Scala, SQL.
• Familiarity with Hadoop/Storm/Spark.