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.

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.

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.

New college graduate Device Engineer supporting NAND flash Memory Health. Responsibilities include evaluating devices, analyzing electrical failures, conducting reliability and cycling experiments, performing data-driven root-cause analysis, developing electrical stress and screening methods, and providing process improvement feedback. The role uses DOE, statistical analysis, visualization, and Python automation while collaborating with device, manufacturing, reliability, test, and global engineering teams.

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.

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.

Build and operate production-grade AI data pipelines and financial knowledge services for equities content. Responsibilities include processing text, tables, documents, and multimedia; creating knowledge bases and search indexes; engineering RAG retrieval and citation systems; integrating LLMs and NLP models; managing orchestration, APIs, quality, cost, observability, reliability, and scalable production operations.

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.

Develop user-facing financial AI and equity research algorithms across query understanding, document processing, entity recognition, event detection, retrieval, ranking, and quality evaluation. Build datasets, labeling systems, benchmarks, and production evaluation frameworks. Apply large language models, NLP, machine learning, reinforcement learning, knowledge graphs, and multimodal methods while collaborating with engineers to deploy and continuously optimize financial data and knowledge systems.

Designs and develops content governance platforms, anti-abuse tools, rule engines, and scalable governance pipelines. Integrates recommendation systems, implements content takedown policies, and builds capabilities for content review, risk detection, policy enforcement, and effectiveness analysis. The role addresses spam, fraud, traffic diversion, low-quality content, and black- or gray-market activity while collaborating with product, operations, algorithm, and business teams.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Leads finance transformation by owning core financial processes, modernizing ERP and planning systems, deploying AI and automation, partnering with engineering and data teams, redesigning workflows, establishing controls, and driving organizational adoption. The role requires senior finance leadership, strong systems expertise, hands-on AI transformation experience, process governance, and the ability to translate between finance and technology.

Support product development for homepage, user center, AI-generated interfaces, market pages, onboarding, personalization, and recommendation experiences. Coordinate with engineering, design, data, and business teams; organize requirements; track metrics; support experiments; analyze feedback; and help resolve issues. The role is part of a 3–6 month early-career accelerator program focused on blockchain products and AI-driven user 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.

Drive and exceed territory sales quotas by generating and qualifying opportunities, acquiring and retaining customers, developing cross-sell opportunities, and managing the full sales cycle. Build relationships with C-level stakeholders, channel partners, and resellers while collaborating with sales engineering, marketing, product, and inside sales teams. Maintain Salesforce forecasting and reporting accuracy and develop strong knowledge of Sophos and competitor cybersecurity solutions.

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.

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.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

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 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.

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.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.