Live opening · Posted 1 day ago

LLM Consultant

Sony Research India · India (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanySony Research India
LocationIndia (Remote)
Work modeNo
SourceLinkedin
Listed1 day ago

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About the role

Description supplied by the original job listing.

Sony Research India is driving cutting-edge research and development in various locations around the globe, including laboratories in Japan, the United States, Europe, and Asia. We endeavor to create new technology, products, and services while sustaining Sony Group’s diverse businesses in electronics, entertainment, and financial fields. For our research centre to blaze a trail in the latest technologies, we seek to foster the growth of a diverse pool of research and engineering talent and create a technology talent bank to drive research excellence worldwide. Sony Research India is offering outstanding career opportunities around frontline technologies such as AI and data analytics.
We are looking for a highly motivated applied research consultant who can assist in our research and development efforts on large-scale user engagement predictive models. The ideal
candidate should have prior experience of research on foundation model (or LLM), Deep Learning, and Recommendation Systems. The candidate must demonstrate a strong commitment to research ethics and integrity.
Key Responsibility:
Research and development in adding multiple tasks over a pretrained LLM model.
Contributing to developing and evaluating models (including user engagement foundation model) leveraging pre-trained LLMs.
Work closely with other research scientists, engineers, and product teams fostering a
collaborative and intellectually stimulating environment.
Contribute to millions of OTT platform users towards improving their experience by
leveraging AI capabilities.
Contribute to the research community by sharing insights and participating in external
academic workshops and conferences.
Work Location:
Remote within India.
Duration of the paid contractual role:
The annual paid direct contractual tenure is renewable/extendable on yearly basis.
Ideally this position will start from the October 1st week 2026.
The working hours are from 9:00 to 18:00 (Monday to Friday) full-time.
Essential Education:
Completed a Ph.D or Master's/Bachelor's degree in Computer Science or allied areas.
Must Have Skills & Abilities:
A strong background in applied deep learning and machine learning, both in terms of
conceptual understanding, as well as practical experience.
Good understanding on handling large scale datasets with SQL.
Understanding about current start of the art machine learning literature.
Prior experience in developing large scale prediction and reasoning models.
Strong knowledge and interest in LLMs (fine-tuning, training and using LLMs).
Proficiency in hands-on with Python and one or more popular deep learning framework.
Ability to envision new ideas and proving them through theory and/or experiments.
Knowledge of working on any cloud platform, preferably AWS, is desirable.
Good to Have Skills:
0-1 year of work experience in building and deploying large-scale predictive models
in production.
0-1 year of work experience in LLM/NLP projects within a start-up environment.
Good publication record, with publications in major machine learning conferences
(e.g. NeurIPS, ICML, KDD, AAAI, SIGIR, RecSys, WSDM, ICDM, ECML, etc.).
Our Values:
Dreams & Curiosity: Pioneer the future with dreams and curiosity.
Diversity: Pursue the creation of the very best by harnessing diversity and varying viewpoints.
Integrity & Sincerity: Earn the trust for Sony brand through ethical and responsible conduct.
Sustainability: Fulfil our stakeholder responsibilities through disciplined business practices.
Sony Research India is committed to equal opportunity in all its employment practices, policies and procedures and to ensuring that no worker or potential worker will receive less favourable treatment due to any characteristic protected under applicable local laws.

Work arrangement
No

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