AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
CEO & Co-Founder @ Neural Nurture | Ex-Amazon, Rakuten, NEC | PhD @ Tokyo Tech | MTech @ IIT Delhi | Visiting Scholar @ UC Berkeley
I am a Research Scientist with a PhD in Natural Language Processing from Tokyo Institute of Technology, specialising in linguistic-acceptability modelling. My journey spans both deep academic research and hands-on industry leadership in machine learning, NLP and applied AI. At Rakuten (2021-2023) I led the NLP Group and steered cross-domain initiatives in E-Commerce, Finance and Travel — including keyword ad-bidding optimisation and knowledge-graph based item-attribute extraction. Prior to that, at Amazon Japan (2019-2021) I served as Senior Technical Program Manager in Applied ML, managing global projects across 13 countries and building core NLP infrastructure (e.g., Japanese-tokeniser, sequence-to-sequence ad-generation pipeline). My early career included research roles at NEC Central Research Laboratories (2014-2017) where I developed deep-learning algorithms that achieved up to 95 % speed-ups on CNNs for supercomputers, as well as a visiting scholar stint at UC Berkeley’s Swarm Lab focusing on IoT and vertical mobility. With a foundation in a Computer Science degree from TCET Indore and an M.Tech from IIT Delhi (CGRA compilers under Prof. Anshul Kumar), I bring together high-performance computing, deep learning and NLP to build research-driven, production-ready solutions. I’m passionate about translating academic insight into meaningful business impact, mentoring ML talent, and advancing AI systems that scale. I’m always exploring collaboration opportunities, new challenges at the intersection of research and industry, and ways to leverage intelligent systems for real-world problems. P.S. Check out my website at https://vijaydaultani.github.io/
Tokyo Institute of Technology
Doctor of Philosophy - PhD, Natural Language Processing
April 1, 2021 – April 1, 2025
Indian Institute of Technology, Delhi
Master of Technology (M.Tech.), Computer Science
January 1, 2012 – January 1, 2014
T.C.E.T Indore
Bachelor of Technology (B.Tech.), Computer Science
January 1, 2006 – January 1, 2010
Neural Nurture
CEO & Co-Founder
May 1, 2025 – Present
Indore, Madhya Pradesh, India
Rakuten
Group Manager
October 1, 2021 – July 1, 2023
Tokyo, Japan
Amazon
Sr. Technical Program Manager - Applied ML
August 1, 2019 – September 1, 2021
Greater Tokyo Area
Rakuten
Head of NLP (Natural Language Processing) Team
July 1, 2018 – July 1, 2019
Rakuten
Deep Learning Researcher
February 1, 2017 – June 1, 2018
University of California, Berkeley
Visiting Scholar
November 1, 2015 – December 1, 2015
San Francisco Bay Area
NEC Corporation
Researcher
October 1, 2014 – February 1, 2017
Kawasaki-ku, Kanagawa, Japan
Indian Institute of Technology, Delhi
Teaching Assistant
July 1, 2012 – July 1, 2014
Greater Delhi Area
Accenture
Associate Software Engineer
September 1, 2010 – August 1, 2011
Mumbai Metropolitan Region
Convolutional Neural Networks on SX Supercomputer architecture.
January 1, 2016 – Present
Experimenting deep learning convolutional neural network on SX Supercomputer architecture, inventing ways for optimal hardware utilization for acceleration. Researching new algorithms for convolution operation of CNN.
Elevator Advisory
November 1, 2015 – Present
Giving a optimal advice to the users whether to choose the conventional elevator system or stair case or escalator, by calculating and comparing the service time for each transportation medium like elevator, and staircase.
Parallel Computation using MPI
January 1, 2014 – Present
As a course project for CSV 880: Special Module in Parallel Computation, I implemented following two assignments. • Problem 1: Averaging based computations on a matrix using block-cyclic distribution. • Problem 2: Broadcasting on a 2D Torus using a single spanning tree.
Backend for CGRA using LLVM
July 1, 2013 – Present
Use LLVM to compile the computation intensive code in C into assembly code. A parser to identify data dependencies then parses the assembly code generated by LLVM with Optimization option "-O3" and a DAG representing the data dependency is constructed. After which Instruction Legalization, Scheduling and Mapping on CGRA is performed.
Analyzing Energy Breakdown of Non-Uniform Cache Access (NUCA)
January 1, 2013 – Present
As a Minor Project I analyzed energy breakdown of Non-Uniform Cache Access (NUCA). After generating experiments results, I analyzed the following both in the case of Static and Dynamic NUCA. • Power consumption and Heat generation patterns of NUCA architecture. • Inter-Banks link access patterns for data of NUCA architecture.
Pintos : Operating System framework of 80x86
January 1, 2013 – Present
Pintos is a simple instructional operating system framework for the 80x86 processor architecture from Stanford University. As a course project for Resource management in Computer Science I implemented following modules in the framework of Pintos • Loading and running user programs. • Virtual Memory management. • File system.
Neural Networks for Machine Learning
Coursera
June 24, 2026 – Present
Coursera Mentor Community and Training Course
Coursera
June 24, 2026 – Present
Initiating and Planning Projects
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
1Z0-007 Introduction to Oracle9i:SQL
Oracle
June 24, 2026 – Present
Internet History, Technology, and Security
Coursera
June 24, 2026 – Present
Machine Learning: Clustering & Retrieval
Coursera
June 24, 2026 – Present
Machine Learning
University of Washington
June 24, 2026 – Present
Deep Neural Networks with PyTorch
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Machine Learning: Regression
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Financial Markets
Coursera
June 24, 2026 – Present
Microsoft Certified Professional (MCP)
Microsoft
June 24, 2026 – Present
Machine Learning Foundations: A Case Study Approach
Coursera
June 24, 2026 – Present
Machine Learning: Classification
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across research, large corporations (Amazon, Rakuten), and a startup (Neural Nurture) suggests adaptability to various work environments. Their involvement in global teams (Amazon, Rakuten) and academic collaborations (UC Berkeley, IIT Delhi) indicates an ability to work with diverse cultures. The focus on AI/ML innovation aligns with a forward-thinking, impact-driven culture. However, the projects listed are heavily research-oriented and less focused on traditional backend system development, which might require adjustment for a pure Backend Engineer role.
Soft Skills & Operational Fit
The candidate's experience as a Group Manager and Sr. Technical Program Manager at Rakuten and Amazon, respectively, indicates strong leadership, cross-functional collaboration, and communication skills. Their ability to direct teams, clarify ambiguous issues, and negotiate technical solutions suggests a high operational fit. The co-founding role at Neural Nurture further highlights entrepreneurial drive and strategic thinking.