株式会社ジーニーの求人一覧

【JAPAN AI】Research Engineer, LLM modeling / English

※この求人はギークニアによる求人紹介案件です。応募情報はギークニアに送信されます。
　ご推薦可能な場合、面談後に推薦をさせて頂きます。

雇用形態	正社員
給与	1200万円〜2000万円（年収 12,000,000 円 - 20,000,000円 Monthly: 857,143－1,428,571 (incl. 45h fixed overtime) Stock options available Reviews & bonuses: twice/year OT beyond 45h paid separately Negotiable based on experience and skills ）
勤務地	東京都
勤務地詳細	東京都新宿区西新宿住友不動産新宿オークタワー５/６階
職種	データサイエンティスト【JAPAN AI】Research Engineer, LLM modeling / English 【JAPAN AI】Research Engineer, LLM modeling / English 企画・マーケ
業種	インターネット関連 IT通信インターネット

必須条件

（業務経験1年以上）

業務内容

About JAPAN AI
JAPAN AI, Inc. was established in April 2023 as a group company of Geniee, Inc. (TSE Growth Market) with the mission of dramatically expanding human potential through AI technology. We drive cutting-edge AI R&D both domestically and internationally.
Our ambition goes far beyond building AI chatbots. We are building "the brain of the enterprise" a next-generation core system where AI autonomously executes business operations by integrating all of a company's SaaS tools. With JAPAN AI STUDIO at the center, we are implementing a world where given a database no separate application is needed; AI performs the work and returns only the results.
Through the transformative power of AI, we aim to create new value and contribute to the advancement of society as a whole. Join us in leading AI innovation and shaping a future where technology empowers people to achieve more.
Related URLs
Our Website
Company Introduction Materials
Tech Blog
Careers
Why We're Hiring
JAPAN AI STUDIO aims to function as "the brain of the enterprise" integrating every SaaS tool a company uses and enabling AI agents to autonomously execute hundreds of workflows. However, realizing this vision requires breaking through "frontier challenges" that current agent technology cannot solve:
Reasoning quality limits when searching and integrating information across multiple SaaS platforms
Long-term memory design that retains context across extended business processes
Multimodal handling that unifies text, images, audio, and structured data
Low-latency inference in environments where hundreds of companies operate simultaneously
Over the past year, adoption of LLM-powered agent systems has accelerated rapidly from coding and research to customer support and security. Looking ahead to a future where AI agents handle increasingly complex tasks end-to-end or in collaboration with humans, JAPAN AI is strengthening the team that will:
Build more effective agents for long-horizon tasks
Design coordination mechanisms for agents to collaborate at various scales
and accomplish larger objectives
Solve the necessary challenges novel harness design, infrastructure improvements, fine-tuning to maximize agent performance
Mission
"Solve the problems that make today's agents give up."
Take on frontier challenges that today's AI agents cannot solve. Break through the quality limits of reasoning, retrieval/planning, long-term memory, and tool use. Pave the way through research for a future where hundreds of workflows running on JAPAN AI STUDIO operate smarter, faster, and more safely.
Role & Expectations
As a Research Engineer, you will lead cutting-edge and applied research in AI/LLM/ML:
Conceive, develop, and compare different agent harnesses (memory, context compression, inter-agent communication architectures, etc.)
Design and implement rigorous quantitative benchmarks for large-scale agentic tasks
Support automated evaluation of models and prompts, ensuring quality across the entire lifecycle from training to production
Collaborate with the product organization to solve the hardest challenges in applying agents to products
Create and optimize training data mixes to improve agent task performance and usability
Transfer research outcomes to the Agentic Product Engineer team, raising quality across all products
Writing papers is not the goal. We prioritize applying research to production and delivering results to users in a live environment serving approximately 200 companies.
Why You'll Love This Role
Research that powers "the brain of the enterprise" This is not about improving chatbots. You will build the technical foundation for a next-generation core system where AI autonomously executes operations by integrating all enterprise SaaS and you will do it through research.
Research → Production, directly connected Your methods are immediately deployed to a production environment used by －200 companies. This is not research that ends with a paper you will feel real-world impact.
Cutting-edge AI research in practice Work on the industry's frontier challenges: breaking reasoning quality limits, designing long-term memory, orchestrating multi-agent coordination, and more.
Research and publication, side by side We encourage paper publication and tech blog writing, and actively support collaboration with academic institutions and OSS communities.
Impact through technology transfer Transfer your methods to the Agentic Product Engineer team and exercise leadership in raising quality across all products.
Rapid-growth environment In a startup that has grown to 200+ people and 9 products in just 3 years, you will have significant autonomy in technical decision-making.
Job Description
Agent Research & Development
Conceive, develop, and compare different agent harnesses (memory, context compression, inter-agent communication architectures, etc.)
Research and develop new reasoning, planning, and retrieval methods
Develop technologies for multimodal and long-context handling
Survey, reproduce, and improve upon the latest research papers
Evaluation & Benchmarking
Design and implement rigorous quantitative benchmarks for large-scale agentic tasks
Design synthetic data generation and evaluation benchmarks
Support automated evaluation of models and prompts (across the full lifecycle from training to production)
Production Problem-Solving
Optimize inference latency and cost (quantization, distillation, caching, etc.)
Create and optimize training data mixes
Advance agent evaluation frameworks
Improve quality and tune performance in production environments
Knowledge Transfer & Outreach
Transfer technology and mentor the Agentic Product Engineer team
Collaborate with academic institutions and OSS communities
Key Results (KR/Metrics)
Benchmark score improvement rate (internal and public benchmarks)
Number of novel methods shipped to production (per quarter)
Inference latency and cost reduction rate
Number of papers and technical blog posts published
Number of internal knowledge transfers completed
Team Structure
Approximately 120 members are part of the development organization.
Research Engineers work across the following groups:
JAI Lab AI research and development
AI & Model Model training and optimization
Voice & Tel Speech AI and telephony systems
Closely collaborating roles:
Agentic Product Engineer Agent feature development (primary research transfer target)
Agent Harness Engineer Agent execution infrastructure
AI Quality Scientist Evaluation pipeline collaboration
Product Manager Product design and prioritization
You May Be a Good Fit If You
Master's or Ph.D. in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Mathematics, Physics, or related fields
Experience developing complex agentic systems using LLMs
Significant hands-on experience in software engineering and ML
Experience with LLM prompt engineering and/or building products with language models
Experience with large-scale model training and inference using PyTorch or JAX
Deep understanding of LLM and Transformer architectures
Ability to read, reproduce, and improve upon research papers
Strong implementation skills in Python (production-quality code)
Language requirement (at least one of the following):
Japanese: Fluent able to discuss product development without friction
English: Business level
Strong Candidates May Also Have
Experience with large-scale reinforcement learning on language models
Experience designing and implementing multi-agent systems
Publications at top-tier conferences (NeurIPS, ICML, ACL, EMNLP, or equivalent)
Hands-on experience implementing alignment techniques such as RLHF or DPO
Experience with multimodal models (e.g., Vision-Language models)
Background in agent evaluation or AI safety research
Ph.D. in CS, ML, NLP, or a related field
Ability to communicate research findings in English
Tech Stack
Languages: Python (research / framework), TypeScript / React / Next.js (frontend) / NX
ML/AI: PyTorch, JAX, Transformers, vLLM, Weights & Biases
Infrastructure: GCP (containers / K8s), Docker
Tools: Slack, Confluence, Linear, Google Workspace, GitHub, Notion
AI Dev Support: Claude Code MAX Plan, Cursor, ChatGPT, Devin
Hardware: Mac (Apple Silicon), dual monitors
Learning & Development Support
AI Tool Usage Support
Company covers the cost of using AI tools such as JAPAN AI SaaS services, Cursor, ChatGPT, Claude, etc.
Development Tool Support
If a desired development tool is paid, the cost is covered (up to 30,000 per year)
Book Purchase Assistance
Company covers the cost of purchasing books for learning, such as technical books (up to 30,000 per half-year)
Language Learning / Qualification Support
Company covers the cost of Japanese or English learning programs and qualification acquisition
Refresh Allowance
Company covers the cost of services used for personal refreshment (up to 5,000 per month)
e.g., gym, yoga, chiropractic, aquarium, movies, theme park tickets, etc.
Housing Allowance
Housing allowance provided for those living in designated areas (up to 30,000 per month)

求人詳細

■職種 / 募集ポジション

【JAPAN AI】Research Engineer, LLM modeling / English

■求人タイトル

【JAPAN AI】Research Engineer, LLM modeling / English

■雇用形態
正社員

■給与
年収 12,000,000 円 - 20,000,000円
Monthly: 857,143－1,428,571 (incl. 45h fixed overtime)
Stock options available
Reviews & bonuses: twice/year
OT beyond 45h paid separately
Negotiable based on experience and skills

■勤務地
東京都新宿区西新宿住友不動産新宿オークタワー５/６階

■Work Style
Hybrid work : 3 days in office, 2 days remote
Flexible working hours : Core time is negotiable
Flexibility : Future consideration for more flexible work styles is possible

■Hiring Process
1. Application Review
2. Homework
3. Interviews (45 rounds)
4. Offer

A reference check will be conducted prior to the final interview.

■仕事についての詳細

＜About JAPAN AI＞
JAPAN AI, Inc. was established in April 2023 as a group company of Geniee, Inc. (TSE Growth Market) with the mission of dramatically expanding human potential through AI technology. We drive cutting-edge AI R&D both domestically and internationally.
Our ambition goes far beyond building AI chatbots. We are building "the brain of the enterprise" a next-generation core system where AI autonomously executes business operations by integrating all of a company's SaaS tools. With JAPAN AI STUDIO at the center, we are implementing a world where given a database no separate application is needed; AI performs the work and returns only the results.
Through the transformative power of AI, we aim to create new value and contribute to the advancement of society as a whole. Join us in leading AI innovation and shaping a future where technology empowers people to achieve more.
Related URLs
Our Website
Company Introduction Materials
Tech Blog
Careers

＜Why We're Hiring＞
JAPAN AI STUDIO aims to function as "the brain of the enterprise" integrating every SaaS tool a company uses and enabling AI agents to autonomously execute hundreds of workflows. However, realizing this vision requires breaking through "frontier challenges" that current agent technology cannot solve:
Reasoning quality limits when searching and integrating information across multiple SaaS platforms
Long-term memory design that retains context across extended business processes
Multimodal handling that unifies text, images, audio, and structured data
Low-latency inference in environments where hundreds of companies operate simultaneously
Over the past year, adoption of LLM-powered agent systems has accelerated rapidly from coding and research to customer support and security. Looking ahead to a future where AI agents handle increasingly complex tasks end-to-end or in collaboration with humans, JAPAN AI is strengthening the team that will:
Build more effective agents for long-horizon tasks
Design coordination mechanisms for agents to collaborate at various scales
and accomplish larger objectives
Solve the necessary challenges novel harness design, infrastructure improvements, fine-tuning to maximize agent performance

＜Mission＞
"Solve the problems that make today's agents give up."
Take on frontier challenges that today's AI agents cannot solve. Break through the quality limits of reasoning, retrieval/planning, long-term memory, and tool use. Pave the way through research for a future where hundreds of workflows running on JAPAN AI STUDIO operate smarter, faster, and more safely.

＜Role & Expectations＞
As a Research Engineer, you will lead cutting-edge and applied research in AI/LLM/ML:
Conceive, develop, and compare different agent harnesses (memory, context compression, inter-agent communication architectures, etc.)
Design and implement rigorous quantitative benchmarks for large-scale agentic tasks
Support automated evaluation of models and prompts, ensuring quality across the entire lifecycle from training to production
Collaborate with the product organization to solve the hardest challenges in applying agents to products
Create and optimize training data mixes to improve agent task performance and usability
Transfer research outcomes to the Agentic Product Engineer team, raising quality across all products
Writing papers is not the goal. We prioritize applying research to production and delivering results to users in a live environment serving approximately 200 companies.

＜Why You'll Love This Role＞
Research that powers "the brain of the enterprise" This is not about improving chatbots. You will build the technical foundation for a next-generation core system where AI autonomously executes operations by integrating all enterprise SaaS and you will do it through research.
Research → Production, directly connected Your methods are immediately deployed to a production environment used by －200 companies. This is not research that ends with a paper you will feel real-world impact.
Cutting-edge AI research in practice Work on the industry's frontier challenges: breaking reasoning quality limits, designing long-term memory, orchestrating multi-agent coordination, and more.
Research and publication, side by side We encourage paper publication and tech blog writing, and actively support collaboration with academic institutions and OSS communities.
Impact through technology transfer Transfer your methods to the Agentic Product Engineer team and exercise leadership in raising quality across all products.
Rapid-growth environment In a startup that has grown to 200+ people and 9 products in just 3 years, you will have significant autonomy in technical decision-making.

＜Job Description＞
Agent Research & Development
Conceive, develop, and compare different agent harnesses (memory, context compression, inter-agent communication architectures, etc.)
Research and develop new reasoning, planning, and retrieval methods
Develop technologies for multimodal and long-context handling
Survey, reproduce, and improve upon the latest research papers
Evaluation & Benchmarking
Design and implement rigorous quantitative benchmarks for large-scale agentic tasks
Design synthetic data generation and evaluation benchmarks
Support automated evaluation of models and prompts (across the full lifecycle from training to production)
Production Problem-Solving
Optimize inference latency and cost (quantization, distillation, caching, etc.)
Create and optimize training data mixes
Advance agent evaluation frameworks
Improve quality and tune performance in production environments
Knowledge Transfer & Outreach
Transfer technology and mentor the Agentic Product Engineer team
Collaborate with academic institutions and OSS communities

＜Key Results (KR/Metrics)＞
Benchmark score improvement rate (internal and public benchmarks)
Number of novel methods shipped to production (per quarter)
Inference latency and cost reduction rate
Number of papers and technical blog posts published
Number of internal knowledge transfers completed

＜Team Structure＞
Approximately 120 members are part of the development organization.
Research Engineers work across the following groups:
JAI Lab AI research and development
AI & Model Model training and optimization
Voice & Tel Speech AI and telephony systems
Closely collaborating roles:
Agentic Product Engineer Agent feature development (primary research transfer target)
Agent Harness Engineer Agent execution infrastructure
AI Quality Scientist Evaluation pipeline collaboration
Product Manager Product design and prioritization

＜You May Be a Good Fit If You＞
Master's or Ph.D. in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Mathematics, Physics, or related fields
Experience developing complex agentic systems using LLMs
Significant hands-on experience in software engineering and ML
Experience with LLM prompt engineering and/or building products with language models
Experience with large-scale model training and inference using PyTorch or JAX
Deep understanding of LLM and Transformer architectures
Ability to read, reproduce, and improve upon research papers
Strong implementation skills in Python (production-quality code)
Language requirement (at least one of the following):
Japanese: Fluent able to discuss product development without friction
English: Business level

＜Strong Candidates May Also Have＞
Experience with large-scale reinforcement learning on language models
Experience designing and implementing multi-agent systems
Publications at top-tier conferences (NeurIPS, ICML, ACL, EMNLP, or equivalent)
Hands-on experience implementing alignment techniques such as RLHF or DPO
Experience with multimodal models (e.g., Vision-Language models)
Background in agent evaluation or AI safety research
Ph.D. in CS, ML, NLP, or a related field
Ability to communicate research findings in English

＜Tech Stack＞
Languages: Python (research / framework), TypeScript / React / Next.js (frontend) / NX
ML/AI: PyTorch, JAX, Transformers, vLLM, Weights & Biases
Infrastructure: GCP (containers / K8s), Docker
Tools: Slack, Confluence, Linear, Google Workspace, GitHub, Notion
AI Dev Support: Claude Code MAX Plan, Cursor, ChatGPT, Devin
Hardware: Mac (Apple Silicon), dual monitors

＜Learning & Development Support＞
AI Tool Usage Support
Company covers the cost of using AI tools such as JAPAN AI SaaS services, Cursor, ChatGPT, Claude, etc.
Development Tool Support
If a desired development tool is paid, the cost is covered (up to 30,000 per year)
Book Purchase Assistance
Company covers the cost of purchasing books for learning, such as technical books (up to 30,000 per half-year)
Language Learning / Qualification Support
Company covers the cost of Japanese or English learning programs and qualification acquisition
Refresh Allowance
Company covers the cost of services used for personal refreshment (up to 5,000 per month)
e.g., gym, yoga, chiropractic, aquarium, movies, theme park tickets, etc.
Housing Allowance
Housing allowance provided for those living in designated areas (up to 30,000 per month)

■Work Style
Hybrid work : 3 days in office, 2 days remote
Flexible working hours : Core time is negotiable
Flexibility : Future consideration for more flexible work styles is possible

■Hiring Process
1. Application Review
2. Homework
3. Interviews (45 rounds)
4. Offer

A reference check will be conducted prior to the final interview.

【JAPAN AI】Research Engineer, LLM modeling / English