Top Machine Learning Jobs in Tokyo

Manage and grow relationships with academic and government customers using legal information and technology solutions. Drive onboarding, training, adoption, renewals, retention, upselling, cross-selling, and customer satisfaction. Analyze usage trends, negotiate renewals, execute retention initiatives, run user events and webinars, respond to inquiries, and track account activity in Salesforce while collaborating with Sales, Marketing, Customer Success, and Proposition teams.

Develops enterprise solutions for human resources and media clients in partnership with Account Executives. Responsibilities include understanding business challenges, planning system implementations, creating and delivering customized AI and Agent demos, preparing solution designs and proposals, developing industry-specific sales plays and demos, and supporting seminars and events through presentations and demonstrations.

Own an AI investing product vertical end to end, including strategy, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Incorporate KYC, transaction monitoring, privacy, licensing, and other regulatory requirements. Apply AI with evaluation, safeguards, and human oversight while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own robotaxi programs from vehicle and fleet readiness through launch and in-market scaling in Japan. Coordinate autonomy, vehicle software and hardware, operations, safety, engineering, and local partners. Manage dependencies, risks, delivery rhythms, stakeholder communications, metrics, and continuous improvement while supporting on-the-ground operations and local vehicle programs in a safety-critical, cross-cultural environment.

Drive manufacturing revenue and pipeline growth across Japan by selling NVIDIA hardware and software. Build customer, OEM, channel, and ecosystem partner relationships; develop go-to-market strategies and business models; manage opportunities, forecasting, and reporting; and coordinate global resources. Engage manufacturers and partners to accelerate workloads and create autonomous agent-based manufacturing solutions using NVIDIA AI platforms, digital twins, and related technologies.

Conduct novel research on efficient and scalable deep generative model training and sampling, safe generative AI, memorization mitigation, concept erasing, data attribution, and multimodal representation learning. Implement innovative algorithms, collaborate with internal researchers, analyze large-scale deep learning results, and publish findings as academic papers.

Own full sales cycle in Japan: build pipeline, engage decision makers at app companies, brands and agencies, close new business, and launch customers while collaborating with Growth, Marketing, and Product to exceed quarterly revenue targets.

As a Senior Growth Manager, you will lead strategic account ownership, revenue strategy, and client leadership, ensuring successful outcomes for a portfolio of key advertiser accounts in Japan, driving growth through complex commercial strategies and advanced data storytelling.

Build end-to-end machine learning systems spanning research reproduction, model evaluation, inference infrastructure, backend services, and product interfaces. Design rigorous experiments, evaluation datasets, and verification workflows; analyze model internals; investigate provenance and evasion; and convert findings into reliable production systems with APIs, background jobs, observability, testing, documentation, and user-facing React/TypeScript experiences.

Design and implement high-performance control modules for off-road autonomous vehicles. Characterize vehicle dynamics, close sim-to-real gaps, and build optimal-control solutions (e.g., nonlinear MPC, MPPI). Test controllers on production vehicles and collaborate with customer engineers to deploy robust autonomy under real-world constraints.

Define and manage safety architecture and requirements for autonomy hardware and software. Perform FMEA/FTA/STPA analyses, lead safety architecture development, work with V&V teams, contribute to safety cases, monitor safety performance, and train teams on safety practices.

Hunt and close net-new enterprise AI deals ($500k+ ACV). Build pipeline in target strategic accounts, lead consultative value-based discussions with executives, position IFS AI solutions, and collaborate with regional sales and solution teams to drive recurring revenue.

As a Technical and Specialized Recruiter, you will source and recruit top technical talent for AI roles, focusing on building relationships and managing the full recruiting cycle.

Lead proactive, hypothesis-driven threat hunts across endpoint, network, and cloud environments; research adversary TTPs (MITRE ATT&CK); develop detections, automate analyses with scripting and ML/LLMs; collaborate with detection engineering, SOC, CTI, and IR teams; perform deep technical forensics and telecommunication-specific threat analysis to improve detection and response.

Lead OWNDAYS global finance strategy from Tokyo HQ: drive AI-augmented FP&A, multi-entity budgeting, controllership (Japan GAAP/IFRS), capital and cash management, M&A and store expansion finance, and build a world-class finance team to support aggressive international growth.

Develop and deploy deep learning systems for autonomous driving, including personalized and collaborative driving behaviors. Build model architectures, data pipelines, evaluation frameworks, and production deployment pathways. Curate real-world and synthetic data, improve closed- and open-loop performance, collaborate across autonomy teams, lead technical initiatives, and mentor engineers.

Lead and grow a Japan-based AV engineering team to localise and deliver autonomy features for Japanese roads. Drive end-to-end development, align with HQ and OEMs, hire and mentor engineers across robotics, ML, controls and systems integration, and represent Wayve in technical and product discussions.

Serve as strategic partner and primary contact for enterprise clients, driving ROI from the fraud/AML SaaS platform. Advise on detection performance, ML-based models, rule engines, and best practices; coordinate with Product and Engineering; deliver business reviews, client education, and actionable feedback to reduce fraud and improve operations.

Lead product roadmap and execution for AI-driven on-chain monitoring tools, coordinate cross-functional teams, analyze market and customer feedback, deliver product features on schedule, and communicate with stakeholders to align expectations.

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

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.

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.