Top Machine Learning Jobs in Yokohama

Owns development, customization, validation, and customer approval of automotive camera functions, including object, traffic sign, signal, lane, calibration, and defect detection. Leads requirements management, system analysis, cross-functional coordination, production process support, and field-return investigations. Requires expertise in camera geometry or machine-learning-based computer vision, statistical analysis, numerical algorithm development, digital imaging, and customer-facing technical coordination.

Owns development, customization, validation, and customer approval of automotive camera functions, including object, traffic sign, lane, calibration, and defect detection. Leads requirements management, system analysis, field-return investigations, production-process support, and cross-functional coordination. Requires expertise in camera geometry or machine-learning-based computer vision, numerical algorithm development, digital imaging, statistical analysis, and customer-facing technical communication.

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.

Lead research on improving AI agent training data and evaluations. Manage and mentor research engineers, define research direction, design rigorous experiments, validate data quality, diagnose reward and grading failures, and translate findings into scalable tools, workflows, and standards. Collaborate with engineers, domain experts, and vendors while communicating technical conclusions and tradeoffs clearly.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Provide customer-facing application support for PCB and semiconductor products, serving as the technical interface for process challenges. Support tool demonstrations, product promotion, benchmarking, competitor analysis, feature introductions, and application validation. Develop customer-specific best known methods and application guidelines while collaborating cross-functionally and supporting customers remotely and onsite.

Build privacy and anonymization systems that detect and transform PII, credentials, secrets, and other sensitive information in data used for AI training. Develop detection methods combining rules, statistical models, classifiers, and LLMs; create production data-processing pipelines; evaluate privacy risk and retained utility; and ensure robustness against schema drift, unusual formats, leakage, and adversarial re-identification.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

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.

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.

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.

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.

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 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.

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.

You will develop and optimize machine learning models for EdgeCortix's hardware, collaborating with engineers to meet AI performance goals.

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.