Top Machine Learning Jobs in Japan

Apply and validate ML and LLM systems to extract clinical information from unstructured medical notes, develop and productionize ML-derived datasets, collaborate with clinicians and engineers, perform dataset performance analyses, and provide analytic support to cross-functional stakeholders.

Lead planning, deployment, optimization, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Configure/tune models, develop automation playbooks and Falcon API integrations, troubleshoot AI-related issues, support incident response and threat hunting, deliver AI workshops, and collaborate on customer-facing AI collateral. Travel up to 25% required.

Lead strategic initiatives for yield improvement in DRAM/NAND/HBM technologies, optimizing methods and collaborating with cross-functional teams to enhance processes and tools.

The Global Supplier Manager will lead supplier management efforts, drive cost optimization, and collaborate across teams to enhance supplier performance, involving strategic sourcing and potential AI solutions.

The Director, Strategic Response and Recovery leads high-stakes customer support for Japanese clients, managing escalations, sentiment analysis, and cross-functional resolution efforts, while enhancing stakeholder relationships and operational goals.

Lead data analytics and ML/AI initiatives for DRAM production: data operations, automation, visualization, and decision support. Develop ML/Deep Learning/Code Assist solutions, collaborate cross-functionally, and drive large projects with sub-leadership in semiconductor manufacturing contexts.

Lead and execute internal audits (SOX, AML, key risk audits) across the region; plan audits, supervise teams, perform testing and root-cause analysis, prepare clear reports, present findings to management, and apply data analytics, automation and emerging technologies to improve audit effectiveness and efficiency.

Lead recruitment and engagement of Japanese startups for NVIDIA Inception, develop ecosystem and VC relationships, evangelize NVIDIA technologies, coordinate cross-functional teams, route startups to business units, and support sell-with/sell-to activities to accelerate adoption of NVIDIA platforms.

Lead pre-sales discovery and solution design for AspenTech APM across Oil & Gas and Chemicals in Japan. Engage customers, build platform-based solutions (APM, data historian, APC, MES, Data Fabric), create proposals and scopes, support sales campaigns, and drive pipeline with technical and business value articulation. Frequent travel within Japan and regional/global engagements.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

Serve as primary customer contact for high-value accounts, grow relationships, train and support product use, troubleshoot technical/business issues, escalate as needed, drive account growth with sales, and apply data analytics and AI/ML to deliver insights, automation, and executive-ready outputs.

Lead data strategy and delivery for Japan & South Korea, owning analytics portfolio, building AI/ML capability, driving advanced modeling, delivering data products, establishing governance, and advising OU leadership to convert data into business value.

Lead design, build, and scale Coke ON platform features using cloud-native, microservices, and event-driven patterns. Collaborate with product, architecture, data, integration, and security teams to deliver secure, observable, and performant front-end and back-end solutions, integrate AI/analytics, reduce technical debt, and drive engineering best practices (CI/CD, automated testing, DevSecOps).

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Work with customers to design, implement, and optimize quantum control workflows on real hardware. Troubleshoot experiment integration, develop Python-based tools, automate calibrations, provide technical guidance, and collaborate with product, R&D, and hardware teams to scale quantum experiments.

Lead the technical strategy for public sector accounts in Japan. Design solutions, ensure compliance, and mentor others in leveraging data and AI.

Design and implement production-quality C++ vehicle control and estimation software using Model Predictive Control and control theory. Translate high-level requirements into implementable designs, negotiate implementation details, and validate performance from unit tests through integrated simulation and vehicle tests.

Own a payments/finance product vertical end-to-end: define strategy, roadmap, and metrics; shape technical design for money movement correctness, reliability, and compliance; apply and evaluate AI/LLM features; coordinate engineering, design, compliance, operations, treasury and finance; ship feature-complete work behind flags and clear external partner and regulatory gates.

Lead development of real-time 3D display rendering algorithms (especially CGH), implement and optimize GPU/ shader/CUDA code, integrate algorithms into game engines, apply machine learning, collaborate with academic and industry partners, and prototype display applications for PlayStation.

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 and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

As an ML Application Engineer, you'll run projects with customers in engineering, applying machine learning to optimize workflows and provide training.

Develop and implement data science and machine learning models for credit risk; analyze complex datasets; ensure data quality and integrity; collaborate with stakeholders; optimize data processes and perform advanced statistical analysis and reporting.