Top Machine Learning Jobs in Nagoya

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.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Apply operations research, mathematical modeling, optimization, simulation, and statistical analysis to support defense decision-making. Develop quantitative models, decision-support tools, and simulations to evaluate concepts, wargames, and system performance. Collect and analyze multi-source data, optimize cost/schedule/logistics models, collaborate with stakeholders, and present findings to senior leadership to improve mission effectiveness and readiness.

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 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.

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 enterprise sales efforts across a territory: prospect, close new customers, expand existing accounts, manage renewals, and coordinate pre/post-sales to deliver DataRobot AI solutions while maintaining pipeline and forecasts in CRM.

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.

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.

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 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.

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.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

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.

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.

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 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.

Lead technical validation of security solutions, deliver product demos, partner with sales, address objections, stay updated on AI security trends, and travel throughout the sales territory.