Job Description:
At Rakuten, we pride ourselves on providing a genuine, immersive experience that has a direct impact on company objectives. You will do meaningful work, and with us, you'll be a true member of the team. We are also invested in your growth as an individual and professional. Please visit rakuten.us and our Muse profile to learn more about Rakuten's culture and values.
Business Unit Introduction:
Our Technology Services Division (TSD) is at the forefront of Rakuten's AI and Data initiatives, playing a pivotal role in enhancing the user experience and operational efficiency across our diverse portfolio. We are dedicated to developing cutting-edge services in areas such as Search, Recommendation, Advertising and Marketing Optimization, Inventory and Price Optimization, Data and Analytics, Conversation AI, and Rakuten AI for Business. Our team is passionate about incubating new ideas and laying the groundwork for the future.
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We are excited to offer a unique program designed for college students passionate about AI and Data Science. This program is an excellent opportunity for those who are eager to apply their academic knowledge to real-world challenges, gain hands-on experience, and contribute to pioneering AI and Data projects within Rakuten.
This program is not only about learning technical and product skills but also about pushing boundaries, being proactive, building relationships, and connecting technology with business and users. It offers a unique blend of bold innovation and thoughtful execution working with members across our global remit, underlined by a commitment to community contribution and personal growth.
Join us at Rakuten to embark on a journey of learning, innovation, and contribution. Together, we can explore the vast potential of AI and Data Science to enhance our services and impact the world positively.
JOB SUMMARY
Rakuten's Tech Service Division is looking for Research Science students to join the team and to work with members across our global remit. RIT-Boston is calling for individuals who have strong expertise in the fields of Natural Language Processing (NLP) and Machine Learning (ML). As a part of our program, you will get to work with a mentor in a research project in the areas of automatic product catalog generation and augmentation with or without user feedback.
KEY RESPONSIBILITIES
- Conduct state-of-the-art research to advance the science and technology of the core components of our services by conducting research on sequence prediction models for NLP, large-scale neural language models, large-scale hierarchical classification models, natural language understanding, and deep learning methods for mining product catalogs
- Contribute to building large-scale NLP pipeline frameworks for training ML algorithms and deployment of ML models as services for business units to consume, and analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
- Develop novel algorithms and corresponding systems, leveraging various AI and ML techniques.
- Collaborate with researchers and engineers across diverse disciplines, including communicating research plans, progress, and results.
- Publish your research in top tier NLP and ML conferences and file patents
QUALIFICATIONS
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Strong knowledge in natural language processing, specifically in language analysis technologies (e.g., word segmentation, word embeddings, PoS tagging, named entity recognition, parsing, or machine translation)
- Strong knowledge in machine learning and/or data mining
- Knowledge of open source NLP and ML software, especially major deep learning frameworks such as Tensorflow and Pytorch
- Knowledge of research and building systems based on machine learning and/or deep learning methods
- Strong programming skills in Python, C/C++ and/or Java
- Strong analytical and quantitative problem-solving ability, and related conceptual skills
- Excellent communication (written and verbal) skills, collaboration skills and is a team player
- Ability to prioritize tasks to meet deadlines
- Ability to work independently and collaboratively in a team
- Experience and knowledge of manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources for large-scale training is preferred
MINIMUM REQUIREMENTS
- Currently enrolled full-time and pursuing a PhD degree in Machine Learning, Natural Language Processing, Computer Science or related technical field
- Research experience in NLP, ML, or data/text mining
- Academic publications in top-tier peer-reviewed international conferences/journals
NAACL-HLT, ACL, EACL, EMNLP, CoNLL, COLING, IJCAI, SIGIR, WWW (Web), WSDM, ICML, NeuRIPS, JMLR, NIST Tracks in NLP, AAAI, CIKM, KDD, AISTATS, ICLR, UAI, COLT, ICDM, etc.
Five Principles for Success
Our worldwide practices describe specific behaviors that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.
Always improve, Always Advance - Only be satisfied with complete success - Kaizen
Passionately Professional - Take an uncompromising approach to your work and be determined to be the best
Hypothesize - Practice - Validate - Shikumika - Use the Rakuten Cycle to succeed in unknown territory
Maximize Customer Satisfaction - The greatest satisfaction for our teams is seeing their customers smile
Speed!! Speed!! Speed!! - Always be conscious of time - take charge, set clear goals, and engage your team
Rakuten provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type. Rakuten considers applicants for employment without regard to race, color, religion, age, sex, national origin, disability status, genetic information, protected veteran status, sexual orientation, gender, gender identity or expression, or any other characteristic protected by federal, state, provincial or local laws.