Top Artificial Intelligence Jobs in Tokyo

Partner with strategic startup customers to prototype, build, and scale generative AI applications on the OpenAI API. Provide technical guidance, experiment with prototypes, synthesize product/model feedback, publish best practices, and build relationships across the startup ecosystem to accelerate customer impact.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.

Customer-facing AI engineer who builds and productionizes GenAI applications (RAG, multi-agent systems, Text2SQL, fine-tuning). Own production rollouts, advise customers, present externally, and influence product roadmap while collaborating cross-functionally.

Lead customers to design and integrate accelerated simulation and AI pipelines for digital twins using NVIDIA Omniverse libraries; perform architecture consulting, build prototypes and proofs-of-concept, coordinate cross-functional teams, and drive adoption of simulation workflows in cloud and on-prem environments.

Develop and validate next-generation graphics (including AI-enabled techniques) for PlayStation SDK by creating game-format demos and samples using Unreal Engine and in‑house engines. Implement shaders and post-effects, collaborate with artists and cross-functional teams, and participate in research-to-implementation of GPU and AI/ML graphics techniques.

Embed with strategic enterprise customers to prototype and ship full-stack AI and agentic applications, drive production readiness, advise on AI strategy and governance, codify repeatable solution patterns, and mentor internal teams.

Partner with customers to design, prototype, and deploy AI-enabled cybersecurity workflows using OpenAI models and tooling. Lead discovery across AppSec, cloud security, SOC/IR, detection engineering, and vulnerability management, build demos and pilots, define success criteria and safety boundaries, and produce reusable playbooks and product feedback.

Design and implement complex backend services for Binance Square. Collaborate with product, DevOps, and QA to deliver high-quality microservices, promote engineering best practices, and perform code reviews.

Early-career intern will support AI projects for compliance and risk (KYC, KYB, EDD). Tasks include testing and optimizing LLM/Agent workflows, reviewing prompts and model outputs, documenting findings and edge cases, supporting small-scale implementations, and performing operational analysis to improve processes.

Early-career full stack engineer role to build end-to-end product features, integrate AI coding tools into the workflow, mentor peers, improve cross-team efficiency, and contribute across the product lifecycle from design through deployment.

Build and maintain full-stack web applications using React/Vue frontends and Java/Spring Cloud microservices. Design and consume REST/AI model APIs, work with SQL and NoSQL databases, use AI-assisted development tools, own features end-to-end, collaborate across product and design, ensure high-quality UI/UX, write tests, and contribute to documentation and architecture.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Early-career research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

Develop and maintain scalable backend services and APIs, collaborate with frontend developers, and lead new features and infrastructure improvements.

Embed with enterprise clients to design, build, and operationalize production agentic AI solutions. Scope use cases, write production code, integrate with enterprise systems, implement retrieval pipelines, guardrails, evaluation suites and observability, and manage cutover, handover, and escalation support while producing reusable patterns and architectures.

Lead Japan Agentic Sales and Presales teams to sell advanced digital and AI solutions (conversational AI, IVA, knowledge management) with or alongside CXone. Develop territory plans, drive revenue growth, recruit and manage team, identify opportunities, collaborate cross-functionally, analyze market trends, and report sales performance.