【JAPAN AI】Research Engineer, LLM modeling / English
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(https://japan-ai.co.jp/)
- Company Introduction Materials(https://www.docswell.com/s/geniee/Z828R2-japan-ai_company-deck#p1)
- Tech Blog(https://engineering.japan-ai.co.jp/)
- Careers(https://japan-ai.co.jp/recruit/)
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)
職種 / 募集ポジション
JAPAN AIResearch 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
163-6006 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 (4-5 rounds)
4. Offer
A reference check will be conducted prior to the final interview.
会社情報
会社名株式会社ジーニー
事業内容
・広告プラットフォーム事業
・マーケティングSaaS事業
・デジタルPR事業
設立年月日
2010年4月14日
代表者
代表取締役社長 工藤 智昭
資本金
100百万円（連結、2025年3月末現在）
従業員数
877名（連結、2025年3月末現在）
本社所在地
東京都新宿区西新宿6-8-1 住友不動産新宿オークタワー5/6階
就業時間
10:00～19:00
※土日祝は休業日となります
※出向の場合は、出向先の規程に準じます
福利厚生
待遇・福利厚生
<正社員>
・書籍購入補助（半期 30,000円まで）
・リフレッシュ手当（毎月 5,000円まで）
・部活動手当（毎月5,000円まで）
・家賃手当（当社指定の駅を対象とし毎月30,000円まで）
・シャッフルランチ/ディナー（四半期に一度ランチ1,000円まで、ディナー5,000円まで）
・資格取得支援制度、英語学習支援制度（業務に必要な場合のみ）
・リフレッシュ休暇制度（3年間継続勤務した社員へ毎年付与される特別休暇 2日）
・定期健康診断（年1回）
・従業員持株会
<契約社員>
・書籍購入補助（半期 30,000円まで）
・リフレッシュ手当（毎月 5,000円まで）
・部活動手当（毎月5,000円まで）
・シャッフルランチ/ディナー（四半期に一度ランチ1,000円まで、ディナー5,000円まで）
・リフレッシュ休暇制度（3年間継続勤務した社員へ毎年付与される特別休暇 2日）
・定期健康診断（年1回）
保険
・社会保険完備
諸手当
・交通費全額支給
代表プロフィール
早稲田大学大学院卒業後、株式会社リクルート（現 株式会社リクルートホールディングス）へ入社。2010年4月株式会社ジーニーを創業、代表取締役社長に就任。2023年4月には戦略的AIカンパニーJAPAN AI株式会社を設立し、同社の代表取締役社長を兼任している。
企業成長ランキング
- Financial Times社発表のアジア成長企業ランキング2020を受賞
Financial Times社とStatista社が、アジア太平洋地域12カ国5,000万以上の企業を対象に実施した調査で、飛躍的活躍を遂げた企業500社に選出されました。
休日休暇
完全週休二日制
所定休日：土・日・祝日
休暇：年次有給休暇、夏季休暇（3日）、年末年始休暇（12月31日〜1月3日）、慶弔休暇
グループ会社
CATS株式会社（日本）
JAPAN AI株式会社（日本）
ソーシャルワイヤー株式会社（日本）
Geniee International Pte., Ltd.（シンガポール）
Geniee Vietnam Co., Ltd.（ベトナム）
PT. Geniee Technology Indonesia（インドネシア）
PT. Adstars Media Pariwara（インドネシア）
Geniee US Inc.（米国）
Geniee Software India Pvt. Ltd.（インド）
GENIEE ADTECH - FZCO（UAE）
備考
・試用期間
正社員/契約社員：1か月
・受動喫煙対策
敷地内禁煙（屋外に喫煙場所設置）
・従事すべき業務の変更の範囲
会社の定める業務
・就業の場所の変更の範囲
会社の定める場所
・有期労働契約を更新する場合の基準に関する事項（通算契約期間又は更新回数の上限を含む）
更新の上限なし