Top Artificial Intelligence Jobs in Nagoya

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.

Lead a team designing, delivering, and scaling AI and automation solutions across Azure and Microsoft 365. Manage hybrid identity, Azure operations, M365 administration, security/compliance, on-prem servers, vendor relations, and AI strategy (Copilot, OpenAI, Cognitive Services). Oversee governance, POCs, and enterprise adoption while providing L2/3 support and project delivery.

Lead design and delivery of cloud-native, event-driven platforms and applications. Drive full lifecycle development, champion engineering best practices, implement production-ready solutions, and build AI/LLM capabilities like RAG, embeddings, and model CI/CD across multi-cloud environments.

As a Forward Deployed Engineer, you'll develop solutions integrating AI with customer workflows, build data insights, and guide technical adoption in client environments.

The role requires driving AI-driven solutions within customer teams, ensuring adoption of OutSystems capabilities, and delivering intelligent solutions while embedded in complex environments.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

Own end-to-end Instagram Reels production: ideation, scripting, editing, and delivery. Use AI tools to support ideation and production, test formats, optimize for retention, and stay on top of short-form video trends to grow international audiences.

As an AI Data Expert, review and annotate AI-generated outputs, ensuring cultural relevance and accuracy. Contribute to AI training with original content and detailed feedback while working flexibly as an independent contractor.