Top Machine Learning Jobs in Tokyo

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.

Design, train, optimize, and deploy deep learning models for object detection, tracking, classification, and activity recognition in industrial environments. Lead dataset strategy, annotation, evaluation, architecture, and real-time inference pipelines. Drive the technical roadmap, establish engineering standards, make architectural decisions, and mentor engineers while delivering production computer vision and machine learning systems.

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%.

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.

The Staff/Senior Machine Learning Scientist will design and implement ML models to optimize advertising campaigns, analyze user data, and collaborate with teams for enhanced solutions.

As a Staff/Senior Machine Learning Platform Engineer, you will architect and scale ML infrastructure, manage data pipelines, and mentor junior engineers.

The Senior Machine Learning Scientist will optimize bidding strategies and audience targeting in the advertising cloud ecosystem, utilizing deep learning models to enhance performance.

The Senior Machine Learning Scientist will develop machine learning algorithms to improve advertising effectiveness, drive experiments, and collaborate with stakeholders.

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.

Create and review realistic, locale-specific robotics and natural sciences tasks in Japanese; apply and adapt scoring rubrics; evaluate and score AI and human responses for accuracy, regulatory alignment, and professional quality; produce gold-standard solutions and expert feedback.

Design, own, and lead end-to-end data architecture and pipelines for large-scale multimodal fleet and simulation data. Build canonical datasets, SLAs, monitoring, and self-serve tools to support ML-based motion planning. Mentor engineers, set organization-wide data engineering standards, prototype architectural bets, and collaborate across teams to deliver reliable, discoverable data products.

Lead design, build, and deployment of ML and optimization engines to control BEV charging/discharging, forecast prices/demand/usage, integrate across systems, mentor engineers, and drive reliable production models that minimize household energy costs.

Lead bring-up, administration, and operations of a large GPU/AI training cluster. Serve as bridge between researchers and hardware, ensuring SLURM jobs, parallel filesystems, networking, and monitoring operate reliably. Work across provisioning, storage, VPN/access, and traditional Linux sysadmin tasks; assist with physical racking and on-site datacenter needs. Collaborate closely with a small research team in Tokyo or San Francisco.

Design, build, optimize, and support ML platform systems and tooling for perception, prediction, and planning. Build dataset generation, cloud training and evaluation pipelines, developer-facing frameworks, and deployment tooling to ship ML models into Toyotas AD/ADAS stack. Collaborate with ML teams, optimize processes and infrastructure, and work in a hybrid Tokyo office.

Build and maintain scalable ML platform tooling, pipelines, and infrastructure for perception, prediction, and planning. Enable dataset curation, distributed training, evaluation, deployment, and inference optimization for AD/ADAS systems at scale.

The Senior Machine Learning Scientist will develop algorithms for campaign efficiency, build identify graphs, and improve return on advertising spend using machine learning.

As a Power ML Engineer, you will adapt existing ML models for the Japanese power market, integrate commodity market signals, develop new features, and enhance performance monitoring tools.