Data Scientist

Rakuten is seeking a dynamic and experienced Generative AI with specialized expertise in training Large Language Models (LLMs) and implementing workflows based on Retrieval-Augmented Generation (RAG). As a key member of our AI Solutions team, you will play a pivotal role in architecting and delivering cutting-edge solutions that leverage the power of Rakuten's generative AI technologies. This position requires a deep understanding of language models, particularly LLMs, and a strong proficiency in designing and implementing RAG-based workflows.

You must have deep technical experience working with technologies related to multimodal, Anomaly Detection and Forecasting, image generation, from model fine-tune to prompt engineering. A strong developing machine learning background is preferred, in addition to experience building application and architecture design. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help build AI powered applications for the user.

Key Job Responsibilities

Solve customer problems by creating solutions using our innovative technology for Machine Learning and Deep Learning including Large Language Models, Computer Vision systems, Recommender systems, and Advanced Generative AI systems.

Strong experience and expertise in Machine Learning forTime Series, Deep Learning, Classical machine learning, clustering, dimensionality reduction and Reinforcement learning. Ability to quickly learn and implement state-of-the-art, and the thought process of generating novel ideas.

Model Development and Deployment : Experience in Designing, developing, and optimizing generative models to generate realistic and diverse outputs. Implementing and fine-tune state-of-the-art generative AI architectures to achieve desired performance metrics. Experience in deploying language models in production environments and integrating them into applications, platforms, or services.

Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows and refine foundation model infrastructure to support the deployment of optimized AI models. Implement state-of-the-art optimization techniques, including quantization, distillation, sparsity, streaming, and caching, for model performance enhancements.

Implement strategies for efficient and effective training of LLMs to achieve optimal performance and design and implement RAG-based workflows to enhance content generation and information retrieval.

Research and Development: Stay up-to-date with the latest advancements in generative AI, including LLMs, GPTs, GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other related techniques. Conduct research to identify and develop novel generative models and algorithms.

Qualifications and Skills

Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).

5+ years experience demonstrating an established track record in Deep Learning and Machine Learning; experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch.

Experience working and building ML Solutions in Telecommunication Domain.

Strong analytical and problem-solving skills.

Strong coding development and debugging skills. Including experience with Python, C/C++, Bash, as well as Cloud services, Spark and Linux.

Experience working with DevOps and MLOps including but not limited to Docker/Containers, Kubernetes, and Data Center or Cloud AI deployments.

Ability to multitask effectively in a dynamic environment.

Clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.

Successful candidates will be able to demonstrate a strong desire to share knowledge with clients, partners, and co-workers.

What we look for

Must have sense of ownership for algorithm/product.

Must be comfortable working with senior and junior level colleagues in various cultures.

Must be highly collaborative.

Must be comfortable working with people in different geographies.

Must be comfortable working in diverse/multi-cultural environment

Our commitment to you:

You'll benefit from our network of global communities and collaborative culture that will help you build technical and functional skills and capabilities. And because we serve more than 28 countries industries globally, you'll have the opportunity to develop valuable industry-specific expertise.