Fujitsu’s R&D vision is to create cutting-edge technologies that support society and prioritize the flow of data. Our five key technologies are essential elements for collecting data from all parts of society, transporting it over ultra-high-speed and secure networks, analyzing it with trusted AI, converting it into value, and returning it to society. Central to realizing our strategy and vision are the people behind our R&D initiatives. We strive to foster top-notch talent in the innovation process by nurturing skilled individuals equipped to advance this cause with originality and dedication.
Role Purpose As Research Manager/IC:
• Team Leadership: Manage a team of researchers, guiding them in developing innovative
AI solutions, creating research proposals aligned with Fujitsu’s AI strategy, and
collaborating with global teams and stakeholders.
• Project Execution: Lead technical execution and ensure timely delivery of research
projects, support patent filings, and publication in top-tier conferences and journals.
• Hands-on Technical Work: Lead and participate in prototyping, algorithm development,
and mathematical modelling to drive research.
• Business Collaboration: Work with business units to demonstrate new technologies,
create use cases, and validate research outcomes.
• Mentorship and Leadership: Provide thought leadership, address technical challenges,
and mentor the team to develop into future technical leaders.
• Stakeholder Engagement: Regularly update leadership on project progress and help
expand research impact across business units.
• Global and Academic Collaboration: Serve as a domain expert for Global Research and
build partnerships with academic institutions.
• Foster Excellence: Promote best practices to build an impactful, collaborative research
team.
Technical Skills
We are seeking candidates with expertise in the following areas, along with a strong publication
track record in top-tier conferences (e.g., A* conferences):
• Advanced AI Expertise:
o Deep understanding of fundamentals of AI models at theoretical and
implementation level, theoretical machine learning, statistical theory of learning,
AI Agents and multi-agentic systems and related technologies, and their practical
implementation in various domains.
o Previous experience in research around Agentic and multi-agentic technologies
such as self-adaptive, self-evolving, self-learning agents with world models, agentic
memory etc is preferred. Good understanding of training algorithms, protocols and
frameworks for Agentic systems is essential.
o Prior experience of testing Agents and multi-agent system in real-world
environment is desirable.
o Up to date with the latest in AI algorithms & neural architectures (e.g., attention,
transformers, state-space models, etc.) and their application to generative AI
(LLMs), explainable AI, causal reasoning, knowledge representation, concept
discovery & extraction, graph AI, etc. Hands-on training of LLM (SFT, RLHF etc.)
is strongly desirable.
• Desirable: An ideal researcher is one capable of performing multi-disciplinary
research, rapidly learn concepts in new domain, and apply to the problem in hand, is
well-informed with latest conceptual advancements in the overall AI space, and able to
include them in his ideas and project at speed
• Proficient in AI/ML Programming: Advanced skills in coding, working with AI/ML
libraries, and familiar with major AI platforms and tools.
• Strong publication track in top-tier conferences such as ICML, ICLR, NeurIPS, AAAI,
IJCAI, AISTATS, SIGKDD, ACL, NAACL etc. For computer vision domain,
publications in top CV conferences like CVPR, ICCV, ECCV is expected
Experience and additional Expectations
• 7-12 years in core research in a reputed organization in the field of Artificial Intelligence
(AI) or Machine Learning with good publication track record with PhD in a relevant field.
• Experience in leading a research team/large project, some experience working across
global teams, managing remote team members etc.
• Experience creating innovative ideas with potential for intellectual property (IP), marketrelevant
business use-cases.
• Experience working with multiple stakeholders, collaborating with teams spread across
different domains, working in a multi-disciplinary setup
• Excellent communication skills, authoring research papers and presentation skills
• Adaptable, willing to learn new fields and develop new skill sets, fast learner with ability
to convert ideas to practical methods or find innovative solutions to use-cases.