Top Machine Learning Jobs in Tokyo

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 engineering projects, automation and digitization, new product qualification, and machine/process reliability. Manage budgets, timelines, root-cause troubleshooting, maintenance strategy, and integration of advanced manufacturing technologies. Mentor and develop engineering team, ensure safety and compliance, and coordinate with regional/global stakeholders to drive productivity and operational excellence.

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).

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, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

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.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

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.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Work with Product, Business, and Engineering to collect, clean, analyze data, build Python and SQL automation, contribute to internal analytics platforms, assist cloud deployments, and document technical solutions to support decision-making.

Lead o9 planning transformation engagements: run blueprinting workshops, define business requirements and functional design, support data integration from ERPs/PLMs/databases, map user stories to sprints, manage build activities, deliver training, and collaborate with cross-functional teams to ensure successful implementation and value realization. Travel 30–50%.

As a Data Scientist, you will build data pipelines, design fraud detection algorithms, collaborate with clients, and contribute to product development.

Join Spellbrush as a 3D Game Programmer to develop narrative and puzzle games in Unity, focusing on innovative AI-driven experiences, particularly in anime aesthetics.

Lead design, implementation, deployment, and maintenance of production ML systems for document understanding. Build scalable model-serving infrastructure, develop and fine-tune ML models (CV/NLP/OCR), collaborate with product owners, and mentor junior engineers.

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.